Desmoid tumour (DT) is a rare and locally aggressive soft tissue sarcoma characterized by unpredictable clinical course. DT patients standard of care is active surveillance, however 30% of patients progress and need active treatment. Sporadic DTs frequently harbour mutations on β-catenin gene, an immune response key regulator. Biomarkers discriminating high-risk patients and deeper knowledge of DT biology are required to optimize interventional approaches. In my PhD project, I will investigate the β-catenin driven immune/inflammatory features at tumour site and in blood of DT patients by different approaches, including tumour and blood transcriptomic analysis, 3D cultures, circulating immune-cells phenotypical and functional studies, profile of soluble factors (ctDNA and cyto/chemokines).

Epithelioid hemangioendothelioma (EHE) is an ultra-rare, translocated vascular sarcoma characterized by a heterogeneous and not predictable clinical behavior. No standard treatments are available and the response to conventional chemotherapy is extremely poor. This PhD project is part of a more extended project aimed at performing a genomic, epigenetic and proteomic characterization of prospectively collected EHE samples to identify novel biomarkers and new therapeutic targets. More specifically, the project focuses on the generation of EHE translatable models to use for molecularly characterizing this poorly understood disease and for validating novel therapeutic targets, putative biomarkers and determinants of drug resistance. 

Emerging evidence has revealed that several organs and tissues once considered sterile, as lung and breast, harbor a unique microbiota. Recently, it has been reported that the tumor modifies the local microbial composition as compared to the healthy tissue, and that tumor-associated microbiota is involved in many pro-tumoral functions. In my PhD project, I am studying the impact of pulmonary microbiota on the growth of different murine model metastases, focusing on its effect on local immunosuppression. Moreover, I will analyze the microbial composition of human lung and breast tumor tissues to evaluate whether it correlates with the patient clinical outcome.

2-5% of gastrointestinal tumors are due to the presence of an hereditary predisposition mostly related to the presence of a constitutional pathogenic variant in a cancer predisposition gene. For some variants known as variants of unknown significance (VUS), it’s difficult to establish a clinical significance related with the risk of cancer occurence. In my PhD project I will focus on the reassessment of VUS identified in genes of hereditary predisposition to digestive tract tumors and their reclassification through in silico analysis, segregation studies and functional studies to better improve personalized surveillance and risk reduction measures.

Mast cells are immune cells displaying a controversial role in cancer. With my project, I aim to clarify their activity in breast cancer, with a particular focus on luminal and HER2 breast cancer, in which mast cells correlate with worse prognosis. I hypothesize that mast cells might affect breast cancer aggressiveness and therapy resistance through the induction of stem-like traits and the promotion of a luminal phenotype. The understanding of the molecular mechanisms through which mast cells affect disease outcome would improve the efficacy of treatment for patients characterized by high density of infiltrating mast cells.

I am focused on the investigation of the transcription factor ZEB1 in the context of osteosarcoma (OS), which is a rare tumour with an aggressive behaviour occurring mostly in children and adolescents. ZEB1 is often up-regulated in OS where it exerts a crucial role during metastatization. I study its role by inhibiting its expression by CRISPR-Cas9 technology and then evaluating the effects in term of stemness and osteogenic differentiation ability in vitro and the tumorigenic/metastatic potential in vivo, as well as the changes in the composition of tumour immune infiltrate. My studies so far indicate that ZEB1 inhibition impairs several aspects related to OS aggressiveness.

HER2+ breast cancers account for 20% of all breast cancers and are particularly aggressive. Anti-HER2 targeted therapies, such as the humanized monoclonal antibody trastuzumab, considerably ameliorated patients’ outcome overtime. Unfortunately, 50% of patients are not responsive to this drug. My PhD project focuses on exploring the possibility of using miRNAs, small RNAs involved in post-transcriptional gene regulation, as biomarkers and therapeutic tool (as target or drug), to predict and overcome resistance to trastuzumab. The final aim is to improve outcome and quality of life of patients by choosing more carefully the right therapy schedule, avoiding overtreatment and propose alternative strategies.

Radiotherapy induces DNA damage leading to apoptotic cell death. It can also exert both immuno-inhibitory and immuno-stimulatory functions, depending on tumour type and setting. Therefore, combining radiotherapy with immunotherapy has a great potential for cancer patients. Interestingly, in some instance, the activation of an anti-tumour immune response in one treated lesion can mediate the regression of distal metastases, not directly treated, effect called “abscopal”. The aim of my project is to evaluate, in different cancer models, the effect of combining radiotherapy with immunotherapy, locally administered within the tumour, in order to increase both local and systemic (abscopal) anti-tumour immune response.

Immune-checkpoint inhibitors (ICIs) have improved clinical outcomes of patients with advanced Non-Small Cell Lung Cancer (NSCLC). Tumor PD-L1 remains the only clinical predictor biomarker of response to ICIs. Despite the efficacy of ICIs mainly correlates to high PD-L1 expression, also patients with low PD-L1 can benefit from ICIs. Extracellular vesicles (EVs) are membrane-limited particles described as biomarkers and immune mediators in cancer. In my project, I mean to evaluate plasma EVs of advanced low PD-L1 NSCLC patients in order to find biomarkers for combination therapy (chemotherapy plus ICIs) and to investigate their role as regulator of the anti-tumor immune response. 

My studies are focused on therapy-induced cancer senescent cells. At the cellular level, senescence refers to a progression of changes culminating in proliferation arrest, apoptosis resistance and metabolic alterations. The development of senescent cells following cancer therapy can lead to treatment resistance and tumor relapse. However, identifying these cells is challenging due to their high heterogeneity. I aim at developing innovative tools to study senescence at a single cell level in different cell lines, exploring its complexity. My final goal is the set-up of label-free methods that will allow the identification of tumor senescent cells in two- and three-dimensional cultures.

My project aims to improve predictive models for the prediction of toxicity after radiotherapy for prostate cancer by including new information on organs-at-risk (organ sub-regions from dose-maps, new organs such as muscles) and improved dose descriptors (dosiomics on dose maps). In particular, I will develop software to create and analyse dose-surface maps in batch mode (voxel-based analysis and dosiomics) and identify obturator muscles on CTs using mathematical models. The final goal is to detect global and local dose-response relationships for all relevant side effects, using an Italian population (DUE01 trial) for discovery and an international population (REQUITE) for validation.

My project aims to improve the analysis of the huge and complex amount of immunological data obtained with high-throughput flow cytometry. I am developing deep machine learning methods, exploiting unsupervised clustering, to achieve fast and robust analysis by eliminating operator dependency. The main goal is to offer solutions for standardized manipulation of heterogeneous data, ensuring accurate comparisons between samples and simplifying the analysis workflow to save time and effort. This approach leads to a comprehensive understanding of the human immune response and allows the discovery of rare clusters and unknown patterns of immunological data. The expected result is improved clinical work-up due to an integrated, operator-independent analysis workflow.

The role of the microbiome in cancer has gained recognition in recent years. In this project, my objective is to elucidate the microbiome's involvement in Squamous Cell Carcinoma (SCC). This project will use advanced sequencing and bioinformatics techniques to conduct a comprehensive exploration of the microbiome's relationship with SCC, focusing specifically on Lung Squamous Cell Carcinoma (LUSC) and Oral Squamous Cell Carcinoma (OSCC). Through ecological analyses, gene expression profiling, and cytokine assessments, I aim to establish the link between the composition of the microbiota and the progression of SCC. To accomplish this, I will employ a diverse set of omics approaches, including metagenomics, RNA-seq, and miRNA-seq, to delve deep into the microbial factors contributing to the development of SCC. The outcomes of this research have the potential to significantly enhance our understanding of SCC and inform the development of more precise and effective strategies for managing this type of cancer.

In case of small populations, such as rare diseases, a randomised controlled trial might be difficult to realise because the necessary sample size is not achievable. This project aims to explore and optimise the currently available methodologies for design and analysis of small clinical trials. Given the variety of objectives and difficulties a small trial could have, the main goal of this project is to develop a “fit for purpose” approach aimed to define a framework for each possible scenario.

Head and neck cancers are the eighth most lethal cancer in the world and develop in the mucosal linings of the upper aerodigestive tract. Despite the improvements in translational research, the 5-year mortality rate has not changed. Recent improvements in NGS have enabled the whole genome/transcriptome/epigenomics profiling to advance our knowledge. Radiomics consists in the extraction of features from radiological images for prediction. The research hypothesis is that integration of multi-omics may: i) improve prognostic prediction and guidance of optimal treatment choice; ii) reveal radiological features to conduct multi-omics integration in the field of radiogenomics.

Anaplastic thyroid cancer (ATC) is among the deadliest solid tumors, for which no effective treatments are currently available. Several anti-cancer treatments induce senescence (therapy-induced senescence, TIS); unfortunately, TIS cells can fuel many aspects of cancer progression. With my project I aim to understand the role of TIS in ATC, and its interplay with autophagy, a catabolic process which is also often induced by anti-cancer treatments. The project might provide new insights into TIS cells biology, and unveil the possibility to target them by modulating the autophagic process.

Lung cancer is still the deadliest cancer worldwide, mostly because of metastatic dissemination. My research project is focused on the identification and functional analysis of metastatic dissemination predictors in lung cancer patients at early stages of the disease. Recently, it has been noted that primary tumors can promote metastases by educating distant organs through the delivery of extracellular vesicles (EVs), leading to the formation of a good "soil" for metastatic spread called "pre-metastatic niche" (PMN). Thus, I’m carrying out an investigation on circulating EVs and their cargo (miRNAs) from lung cancer patients with the aim of identifying new early biomarkers and elucidating their role in the formation of PMN.

Chimeric antigen receptor (CAR)-T cell therapy is a revolutionary clinical strategy in some hematological malignancies; however, many challenges are still limiting their therapeutic efficacy in solid tumors. For this reason, the objective of my research project is to design and manufacture novel CAR T cells for solid tumor treatment. Particularly, the idea is to re-direct CAR T cells against a non-protein antigen overexpressed on several epithelial solid tumor cells, while absent on normal tissues. Once generated, the second aim is to test both their in vitro and in vivo anti-tumor activity and tumor-specificity.