Systemic mastocytosis: Molecular landscape and implications for treatment

Over the past decade, we have witnessed significant advances in the molecular characterization of systemic mastocytosis (SM). This has provided important information for a better understanding of the pathogenesis of the disease but has also practically impacted the way we diagnose and manage it. Advances in molecular testing have run in parallel with advances in therapeutic targeting of constitutive active KIT, the major driver of the disease. Therefore, assessing the molecular landscape in each SM patient is essential for diagnosis, prognosis, treatment, and therapeutic efficacy monitoring. This is facilitated by the routine availability of novel technologies like digital PCR and NGS. This review aims to summarize the pathogenesis of the disease, discuss the value of molecular diagnostic testing and how it should be performed, and provide an overview of present and future therapeutic concepts based on fine molecular characterization of SM patients

PGE2-Induced IDO1 Inhibits the Capacity of Fully Mature DCs to Elicit an In Vitro Antileukemic Immune Response.

In the last years, dendritic cells (DC) have been evaluated for antitumor vaccination. Although DC-based vaccines have raised great expectations, their clinical translation has been largely disappointing. For these results, several explanations have been proposed. In particular, the concomitant expression by DCs of tolerogenic pathways, such as the immunosuppressive agent indoleamine 2,3-dioxygenase-1 (IDO1), has been demonstrated. The aim of this study is to evaluate both the stimulatory and the tolerogenic feature of monocyte-derived DCs (Mo-DCs) after maturation with PGE2. In particular, the role of IDO1 expression in PGE2-matured Mo-DCs has been addressed. Here we show that PGE2, which is required for full maturation of DCs, is one mediator of DC tolerance by enhancing IDO1. PGE2-mediated expression of IDO1 results in the production of kynurenine, in the generation of Tregs, and in the inhibition of either the allogeneic or the autologous antigen-specific stimulatory capacity of DCs. When pulsed with leukemic lysates and matured with PGE2, DCs are impaired in the induction of IFN-γ secreting CD4(+) and CD8(+) T cells due to IDO1 upregulation. Moreover, the inhibition of IDO1 enhances the antileukemic response. Overall, these results point toward the use of IDO1 inhibitors to enhance the vaccination capacity of DCs, matured with PGE2

Sunitinib Exerts In Vitro Immunomodulatory Activity on Sarcomas via Dendritic Cells and Synergizes With PD-1 Blockade

Background: High-grade sarcomas are a heterogeneous group of aggressive tumors arising in bone and soft tissues. After relapse, treatment options are limited. The multi-targeted receptor tyrosine kinase inhibitors (TKIs) sunitinib and inhibitor of PD-1 (anti-PD-1) nivolumab have shown antitumor activity in selected subtypes. In this study, we examine the role of TKIs and PD-1 based therapy in in vitro cocultures of sarcoma. Methods: The human osteosarcoma (SaOS-2) and synovial sarcoma (SYO-1) cell lines were treated with sunitinib. After cell death and proliferation assessment, expression of PD-L1 was analyzed by flow cytometry. Sunitinib-treated sarcoma cells were cocultured with dendritic cells (DCs), and the phenotype of mature DCs was determined by flow cytometry. Mature DCs were cultured with autologous T cells. PD-1 expression on T cells, their proliferation, T regulatory cell (Tregs) induction and IFN-γ production, before and after nivolumab exposure, were analyzed. Results: Along with its anti-proliferative and direct pro-apoptotic effect on sarcoma cell lines, sunitinib prompted PD-L1 upregulation on sarcoma cells. Interestingly, sunitinib-treated sarcoma cells drive DCs to full maturation and increase their capacity to induce sarcoma-reactive T cells to produce IFN-γ. Conversely, no effect on T cell proliferation and T cell subpopulation composition was observed. Moreover, both bone and synovial sarcoma cell lines induced Tregs through DCs but sunitinib treatment completely abrogated Treg induction. Finally, sarcoma cell lines induced PD-1 upregulation on both effector T cells and Tregs when loaded into DCs, providing a rationale for using PD-1 blockade. Indeed, PD-1 blockade by nivolumab synergized with sunitinib in inducing IFN-γ-producing effector T cells. Conclusions: Taken together, our in vitro data indicate that the treatment of sarcoma cells with sunitinib can exert significant changes on immune cell subsets toward immune activation, leading to DC-based cross-priming of IFN-γ-producing effector T cells and reduced Treg induction. PD-1 blockade with nivolumab has a synergistic effect with sunitinib, supporting the use of TKI and anti-PD-1 approach in sarcomas, and perhaps in other cancers. DC-targeted drugs, including toll-like receptor 3 inhibitors and CD47 inhibitors, are under development and our preclinical model might help to better design their clinical application

BoBafit: A copy number clustering tool designed to refit and recalibrate the baseline region of tumors’ profiles

Human cancer arises from a population of cells that have acquired a wide range of genetic alterations, most of which are targets of therapeutic treatments or are used as prognostic factors for patient's risk stratification. Among these, copy number alterations (CNAs) are quite frequent. Currently, several molecular biology technologies, such as microarrays, NGS and single-cell approaches are used to define the genomic profile of tumor samples. Output data need to be analyzed with bioinformatic approaches and particularly by employing computational algorithms. Molecular biology tools estimate the baseline region by comparing either the mean probe signals, or the number of reads to the reference genome. However, when tumors display complex karyotypes, this type of approach could fail the baseline region estimation and consequently cause errors in the CNAs call. To overcome this issue, we designed an R-package, BoBafit, able to check and, eventually, to adjust the baseline region, according to both the tumor-specific alterations’ context and the sample-specific clustered genomic lesions. Several databases have been chosen to set up and validate the designed package, thus demonstrating the potential of BoBafit to adjust copy number (CN) data from different tumors and analysis techniques. Relevantly, the analysis highlighted that up to 25% of samples need a baseline region adjustment and a redefinition of CNAs calls, thus causing a change in the prognostic risk classification of the patients. We support the implementation of BoBafit within CN analysis bioinformatics pipelines to ensure a correct patient's stratification in risk categories, regardless of the tumor type