Espressione dell'Enzima ad Azione Immunoregolatoria Indoleamina 2,3-Diossigenasi nella Leucemia Mieloide Acuta dell'Adulto: correlazioni Clinico-Biologiche

L’enzima IDO interviene nella via di degradazione del triptofano, essenziale per la vita cellulare; l’iperespressione di IDO favorisce la creazione di un microambiente immunotollerante. Nelle LAM IDO è funzionalmente attivo nelle cellule blastiche e determina l’acquisizione di un fenotipo regolatorio da parte delle cellule T alloreattive; l’espressione della proteina aumenta in modo consensuale con l’evoluzione clinica della patologia. Scopo della Tesi è indagare l’esistenza di una correlazione tra l’iperespressione di IDO da parte delle cellule leucemiche, le caratteristiche di rischio alla diagnosi e l’outcome dei pazienti. Sono stati esaminati 45 pazienti adulti affetti da LAM afferiti all’Istituto di Ematologia di Bologna. I pazienti sono stati stratificati a seconda di: età di insorgenza della leucemia, secondarietà a Mielodisplasia o radio chemioterapia, iperleucocitosi, citogenetica, biologia molecolare (sono state valutate le alterazioni a carico dei geni FLT3 ed NPM). I pazienti sono stati analizzati per l’espressione del gene IDO mediante RT-PCR, seguita da Western Blot, allo scopo di stabilire la presenza di una proteina attiva; successivamente si è proceduto a verificare l’esistenza di una correlazione tra l’espressione di IDO e le caratteristiche di rischio alla diagnosi per identificare una relazione tra l’espressione del gene ed un subset di pazienti a prognosi favorevole o sfavorevole. Dei 45 pazienti adulti affetti da LAM il 28,9% è risultato negativo per l’espressione di IDO, mentre il rimanente 71,1% è risultato positivo ed è stato suddiviso in tre ulteriori categorie, in base ai livelli di espressione. I dati non sembrano al momento suggerire l’esistenza di una correlazione tra l’espressione di IDO e le caratteristiche di rischio alla diagnosi. Nel gruppo di pazienti ad elevata espressione di IDO si riscontra un rate di resistenza alla chemioterapia di induzione più elevato, con una quota di pazienti resistenti pari al 71,4%, contro il 23,1% nel gruppo di pazienti IDO-negativi.

Study of novel natural compounds as potential drugs in the treatment of acute leukemias

Introduction: Among all cancer types leukemia represents the leading cause of cancer death in man younger than 40 years. Single-target drug therapy has generally been highly ineffective in treating complex diseases such as cancer. A growing interest has been directed toward multi-target drugs able to hit multiple targets. In this context, plant products, based on their intrinsic complexity, could represent an interesting and promising approach. Aim of the research followed during my PhD was to indentify and study novel natural compounds for the treatment of acute leukemias. Two potential multi-target drugs were identified in Hemidesmus indicus and piperlongumine. Methodology/Principal Findings: A variety of cellular assays and flow cytometry were performed on different cell lines. We demonstrated that Hemidesmus modulates many components of intracellular signaling pathways involved in cell viability and proliferation and alters gene and protein expression, eventually leading to tumor cell death, mediated by a loss of mitochondrial transmembrane potential, raise of [Ca2+]i, inhibition of Mcl-1, increasing Bax/Bcl-2 ratio, and ROS formation. Moreover, we proved that the decoction causes differentiation of HL-60 and regulates angiogenesis of HUVECs in hypoxia and normoxia, by the inhibition of new vessel formation and the processes of migration/invasion. Clinically relevant observations are that its cytotoxic activity was also recorded in primary cells from acute myeloid leukemia (AML) patients. Moreover, both Hemidesmus and piperlongumine showed a selective action toward leukemic stem cell (LSC). Conclusions: Our results indicate the molecular basis of the anti-leukemic effects of Hemidesmus indicus and indentify the mitochondrial pathways, [Ca2+]i, cytodifferentiation and angiogenesis inhibition as crucial actors in its anticancer activity. The ability to selectively hit LSC showed by Hemidesmus and piperlongumine enriched the knowledge of their anti-leukemic activity. On these bases, we conclude that Hemidesmus and piperlongumine can represent a valuable strategy in the anticancer pharmacology.

Microenvironment and prognostic factors in bone tumors: IDH mutations in chondrosarcoma

Microenvironment in bone tumors is a dynamic entity composed of cells from different origins (immune cells, stromal cells, mesenchymal stem cells, endothelial cells, pericytes) and vascular structures surrounded by a matrix of different nature (bone, cartilage, myxoid). Interactions between cancer cells and tumor microenvironment (TME) are complex and can change as tumor progress, but are also crucial in determining response to cancer therapies. Chondrosarcoma is the second most frequent bone cancer in adult age, but its treatment still represents a challenge, for the intrinsic resistance to conventional chemotherapy and radiation therapy. This resistance is mainly due to pathological features, as dense matrix, scarce mitoses and poor vascularization, sustained by biological mechanisms only partially delucidated. Somatic mutation in the Krebs cycle enzyme isocytrate dehydrogenase (IDH) have been described in gliomas, acute myeloid leukemia, cholangiocarcinoma, melanoma, colorectal, prostate cancer, thyroid carcinoma and other cancers. In mesenchymal tumors IDH mutations are present in about 50% of central chondrosarcoma. IDH mutations are an early event in chondrosarcoma-genesis, and contribute to the acquisition of malignancy through the block of cellular differentiation, hypoxia induction through HIF stabilization, DNA methylation and alteration of cellular red-ox balance. While in gliomas IDH mutations confers a good prognosis, in chondrosarcoma IDH prognostic role is controversial in different reported series. First aim of this project is to define the prevalence and the prognostic role of IDH mutation in high grade central conventional chondrosarcoma patients treated at Istituto Ortopedico Rizzoli. Second aim is the critical revision of scientific literature to understand better how a genomic event in cancer cell can trigger alteration in the TME, through immune infiltrate reshaping, angiogenesis induction, metabolic and methylation rewiring. Third aim is to screen other sarcoma histotypes for the presence of IDH mutation.

Development of machine learning methods for multi-modal biomarkers detection and integration

In medicine, innovation depends on a better knowledge of the human body mechanism, which represents a complex system of multi-scale constituents. Unraveling the complexity underneath diseases proves to be challenging. A deep understanding of the inner workings comes with dealing with many heterogeneous information. Exploring the molecular status and the organization of genes, proteins, metabolites provides insights on what is driving a disease, from aggressiveness to curability. Molecular constituents, however, are only the building blocks of the human body and cannot currently tell the whole story of diseases. This is why nowadays attention is growing towards the contemporary exploitation of multi-scale information. Holistic methods are then drawing interest to address the problem of integrating heterogeneous data. The heterogeneity may derive from the diversity across data types and from the diversity within diseases. Here, four studies conducted data integration using customly designed workflows that implement novel methods and views to tackle the heterogeneous characterization of diseases. The first study devoted to determine shared gene regulatory signatures for onco-hematology and it showed partial co-regulation across blood-related diseases. The second study focused on Acute Myeloid Leukemia and refined the unsupervised integration of genomic alterations, which turned out to better resemble clinical practice. In the third study, network integration for artherosclerosis demonstrated, as a proof of concept, the impact of network intelligibility when it comes to model heterogeneous data, which showed to accelerate the identification of new potential pharmaceutical targets. Lastly, the fourth study introduced a new method to integrate multiple data types in a unique latent heterogeneous-representation that facilitated the selection of important data types to predict the tumour stage of invasive ductal carcinoma. The results of these four studies laid the groundwork to ease the detection of new biomarkers ultimately beneficial to medical practice and to the ever-growing field of Personalized Medicine.