Biology subjects

Pichiorri, F.

Publications and source records attributed to Pichiorri, F..

4 recordsLinked to original sources

bioRxiv2024

Mathematical Modeling Unveils Optimization Strategies for Targeted Radionuclide Therapy of Blood Cancers

Targeted radionuclide therapy is based on injections of cancer-specific molecules conjugated with radioactive nuclides. Despite the specificity of this treatment, it is not devoid of side-effects limiting its use and is especially harmful for rapidly proliferating organs well perfused by blood, like bone marrow. Optimization of radioconjugates administration accounting for toxicity constraints can increase treatment efficacy. Based on our experiments on disseminated multiple myeloma mouse model treated by 225Ac-DOTA-daratumumab, we developed a mathematical model which investigation highlighted the following principles for optimization of targeted radionuclide therapy. 1) Nuclide to antibody ratio importance. The density of radioconjugates on cancer cells determines the density of radiation energy deposited in them. Low labeling ratio as well as accumulation of unlabeled antibodies and antibodies attached to decay products in the bloodstream can mitigate cancer radiation damage due to excessive occupation of specific receptors by antibodies devoid of radioactive nuclides. 2) Cancer binding capacity-based dosing. The rate of binding of drug to cancer cells depends on the total number of their specific receptors, which therefore can be estimated from the pharmacokinetic curve of diagnostic radioconjugates. Injection of doses significantly exceeding cancer binding capacity should be avoided since radioconjugates remaining in the bloodstream have negligible efficacy to toxicity ratio. 3) Particle range-guided multi-dosing. The use of short-range particle emitters and high-affinity antibodies allows for robust treatment optimization via initial saturation of cancer binding capacity, enabling redistribution of further injected radioconjugates and deposited dose towards still viable cells that continue expressing specific receptors. SignificanceMathematical modeling yields general principles for optimization of targeted radionuclide therapy in mouse models of multiple myeloma that can be extrapolated on another cancer models and on clinical setting.

cancer biology↗

bioRxiv2023

Leveraging IFNγ/CD38 regulation to unmask and target leukemia stem cells in acute myelogenous leukemia

Elimination of drug-resistant leukemia stem cells (LSCs) represents a major challenge to achieve a cure in acute myeloid leukemia (AML). Although AML blasts generally retain high levels of surface CD38 (CD38pos), the presence of CD34 and lack of CD38 expression (CD34posCD38neg) are immunophenotypic features of both LSC-enriched AML blasts and normal hematopoietic stem cells (HSCs). We report that IFN-{gamma} induces CD38 upregulation in LSC-enriched CD34posCD38neg AML blasts, but not in CD34posCD38neg HSCs. To leverage the IFN-{gamma} mediated CD38 up-regulation in LSCs for clinical application, we created a compact, single-chain CD38-CD3-T cell engager (CD38-BIONIC) able to direct T cells against CD38pos blasts. Activated CD4pos and CD8pos T cells not only kill AML blasts but also produce IFN{gamma}, which leads to CD38 expression on CD34posCD38neg LSC-enriched blasts. These cells then become CD38-BIONIC targets. The net result is an immune-mediated killing of both CD38neg and CD38pos AML blasts, which culminates in LSC depletion. Statement of significanceThis work represents a potential advancement in the treatment of AML, as it involves the release of IFN-{gamma} by T cells to induce CD38 expression and thus sensitizing leukemia stem cells, which have been resistant to current treatment regimens, to CD38-directed T cell engagers.

cancer biology↗

bioRxiv2019

Daratumumab induces mechanisms of immune activation through CD38+ NK cell targeting

Daratumumab (Dara), a multiple myeloma (MM) therapy, is an antibody against the surface receptor CD38, which is expressed not only on plasma cells but also on NK cells and monocytes. Correlative data have highlighted the immune-modulatory role of Dara, despite the paradoxical observation that Dara regimens decrease the frequency of total NK cells. Here we show that, despite this reduction, NK cells play a pivotal role in Dara anti-MM activity. CD38 on NK cells is essential for Dara-induced immune modulation, and its expression is restricted to NK cells with effector function. We also show that Dara induces rapid CD38 protein degradation associated with NK cell activation, leaving an activated CD38-negative NK cell population. CD38+ NK cell targeting by Dara also promotes monocyte activation, inducing an increase in T cell costimulatory molecules (CD86/80) and enhancing anti-MM phagocytosis activity ex-vivo and in vivo. In support of Daras immunomodulating role, we show that MM patients that discontinued Dara therapy because of progression maintain targetable unmutated surface CD38 expression on their MM cells, but retain effector cells with impaired cellular immune function. In summary, we report that CD38+ NK cells may be an unexplored therapeutic target for priming the immune system of MM patients.

cancer biology↗

bioRxiv2018

Dissecting heterogeneous cell-populations across signaling and diseaseconditions with PopAlign

Single-cell measurement techniques can now probe gene expression in heterogeneous cell populations from the human body across a range of environmental and physiological conditions. However, new mathematical and computational methods are required to represent and analyze gene expression changes that occur in complex mixtures of single cells as they respond to signals, drugs, or disease states. Here, we introduce a mathematical modeling platform, PopAlign, that automatically identifies subpopulations of cells within a heterogeneous mixture, and tracks gene expression and cell abundance changes across subpopulations by constructing and comparing probabilistic models. Probabilistic models provide a low-error, compressed representation of single cell data that enables efficient large-scale computations. We apply PopAlign to analyze the impact of 40 different immunomodulatory compounds on a heterogeneous population of donor-derived human immune cells as well as patient-specific disease signatures in multiple myeloma. PopAlign scales to comparisons involving tens to hundreds of samples, enabling large-scale studies of natural and engineered cell populations as they respond to drugs, signals or physiological change.

bioinformatics↗