Open Positions

We have recently discovered that BACE2-dependent amyloid fibrils are new components of the tumor extracellular environment in metastatic melanoma where they promote cell proliferation through the activation of the transcriptional coactivator YAP, a master sensor of extracellular stiffness (Matafora V et al. Amyloid aggregates accumulate in melanoma metastasis modulating YAP activity. 2020, EMBO Rep).
We have also noticed that the protease BACE2 is overexpressed in several solid tumors (Farris F et al. The emerging role of β-secretases in cancer. J EXP CLIN CANC RES 2021) raising the intriguing hypothesis that it could actively take part in tumor biology.
Moreover, recent data of the lab demonstrate that BACE2 has an active role in lipid metabolism homeostasis.
Aim of this project will be the elucidation of the role of BACE2 in shaping tumor microenvironment. In particular, the student will be involved in the development of highly sensitive proteomics and metabolomics methods able to dissect the proteome and lipidome complexity up to single cell resolution by using cutting-edge imaging and mass spectrometric techniques.

The project will exploit patients- derived models to define new therapeutic vulnerabilities in colorectal cancers (CRC). The candidate will use gene editing approaches to identify the DNA repair landscape of CRC and its impact on tumor cell growth and immune surveillance.

Genome structural variants (SVs) are a hallmark of cancer genomes. SVs and complex chromosomal rearrangements are thought to disrupt the physiological three-dimensional (3D) architecture of the genome, in turn leading to rewiring of key gene regulatory networks that control cell identity and tissue homeostasis. A thorough understanding of how SVs reshape 3D genome organization and gene expression at the single-cell level is currently missing.
In this doctoral project, the student will first work on developing a single-cell multi-omic assay to concurrently detect SVs, map the 3D genome conformation, and measure gene expression in the same cell. Once this method and the computational tools necessary to analyze the resulting data are up-and-running, the student will apply them to chart the SV, 3D genome and transcriptome landscape in colorectal cancer organoids that are being prospectively generated in the group of our collaborator Dr. Andrea Sottoriva in the Computational Biology Centre at Human Technopole.
This is a highly challenging multi-disciplinary project that is especially suited for candidates with a strong interest in working at the intersection between single-cell omics and cancer genomics.

The composition of tumour infiltrating lymphocytes (TILs) can be highly heterogeneous; in particular, a high percentage of exhausted TILs and immunosuppressive Tregs is associated with bad prognosis. The discovery of immune-checkpoint inhibitors actuated a paradigm shift in cancer therapy even though the percentage of refractory patients is still high. Therefore, there is a compelling need to find novel targets to increase responders.
We have recently uncovered a novel mechanism of gene expression that regulate the switch from T cell quiescence to activation. Specifically, in naïve CD4+ T-cells, Long Interspersed Nuclear Elements 1 (LINE1) are spliced as novel exons in alternative transcript variants, dampening the expression of genes required for cellular activation. Moreover, exhausted TIL re-accumulate LINE1-transcripts and their downregulation with anti-sense oligonucleotides (ASOs) restore effector function. Since the accumulation of LINE1-transcripts is critical in TILs and could be reverted by pharmacological targeting, we aim to determining the LINE1-transcripts signature in CD3+ TILs exploiting single-cell full-length short and long read sequencing using de novo transcriptome reconstruction approach. Then, to identify the molecular players that regulate LINE1-transcripts biogenesis in TILs, a Perturb-seq coupled with scRNA-seq will be adopted.
This project could open a novel scenario in cancer immunotherapy providing new therapeutic candidates.

Immunotherapy has radically modified the natural history of many tumors, yet most patients are either resistant to treatment or relapse with resistant disease. Accumulating evidence suggests that the efficacy of cancer immunotherapy relies on antigen-specific activation of T-lymphocytes with anti-tumor activities.
We propose a PhD project in collaboration between T. Bonaldi’s and PG Pelicci’s groups, focused on the MS-based proteomic characterization of antigens involved in the anti-tumor response elicited by antigen-presenting cells (APCs) expressing allogeneic MHC.
This project stems from our ongoing studies on the role of allogeneic MHC in the activation of homeostatic T cell proliferation and anti-tumor responses. Upon optimization of an efficient immuno-peptidomics workflow at the Department of Experimental Oncology of IEO, in collaboration with Dr. L. Santambrogio at Cornell University (NY), the PhD student will carry out a systematic characterization and profiling of peptides bound to MHC molecules from distinct APC types, using the nano- Liquid Chromatography- Mass Spectrometry (nUPLC-MS/MS) platform fully optimized by Bonaldi’s team at IEO. 
The PhD student will learn state-of-the-art MS-proteomics and immuno-peptidomes methodologies, from sample preparation to MS-data analysis, and to integrate proteomics with other -omics data generated within this project. The project involves usage of different mouse/cell models and state-of-the art cellular and molecular biology technologies, thus offering the PhD the unique opportunity of acquiring multi-disciplinary know-how in one of the most innovative field of modern molecular oncology.

A broad number of lncRNAs interact with chromatin providing regulation, yet the function is unknown for the majority of RNAs. Using our RNA and DNA Ligated and Sequenced (RADICL-seq) technology and other complementary genomics / transcriptomics data, we will map and functionally characterize key RNA regulators of chromatin activity/epigenome in cell differentiation and will charaterize the function of top candidates.

SINEUPs are a class of RNAs that enhance translation of the mRNAs that they pairs as antisense RNAs, through the action of a transcribed SINE RNA embedded in the antisense RNA.
The candidate will study the function, structure and interactomes of SINEUP RNAs, searching for mechanistic insights for this fascinating RNA class.

We have developed approaches for profiling single cell transcriptomes centered on sequencing single cell RNAs from 5' ends, which allows simultaneous mapping of regulatory elements wlike promoters and enhancers. We will explore these in a set of brain organoids, including models of neuron infections with SARS-CoV-2.

Gene expression can be regulated at multiple levels. This allows organisms to respond fast to specific cellular stimuli while maintaining a stable internal environment. This regulation can be achieved through chemical marks on DNA, RNA and proteins.
The Casañal Group focuses on the study of RNA modifications, particularly within messenger RNA (mRNA). mRNA marks are involved in essential cellular roles, such as development and stress, and their deregulation is linked to human disorders, including cancer, infertility and depression. Despite their fundamental importance, chemical modifications on mRNA remain poorly understood in mechanistic terms. The Casañal Group combines cryo-EM with biochemical and biophysical methods to understand the structure and mechanisms of the macromolecular machines that add and read out mRNA marks. By understanding how these multi-protein complexes work within the cell, we will gain insight into how they regulate gene expression and how they impact various diseases. This, in turn, will help discover new therapeutic targets for drug development.
Our powerful multi-technique approach offers a unique advantage to succeed in challenging projects and allows our students to learn several state-of-the-art biochemical, biophysical and structural biology techniques. We are part of the Structural Biology Centre at Human Technopole, a new research institute designed from the ground up to facilitate cutting edge research that provides access to excellent infrastructure and core facilities.
We are looking for enthusiastic candidates intrigued by how proteins work, with a keen interest in structural methods and biological mechanisms, to join our interdisciplinary and international team. For more information, visit https://humantechnopole.it/en/research-groups/casanal-group/. For informal enquires contact ana.casanal[at]fht.org.

Transcription factors (TFs) are DNA-Binding proteins which have a prominent role in controlling expression by binding to gene regulatory regions.  TFs can also recruit or otherwise interact with RNA-binding proteins which controls the processing of RNA. The interplay among DNA and RNA binding proteins is a possible source of gene dysregulation and the functional role of cis- and trans-acting genetic alterations requires investigation in this light.

Aim of the project (in collaboration between the Computational Biology Lab at IRCCS E. Medea and the Cancer Genomics and Bioinformatics lab at the University of Milan) is to disentangle the regulatory crosstalk between DNA and RNA proteins and provide the scientific community with a list of binding preference models for both these protein types.

The models will be identified through the application of computational methods, including artificial intelligence approaches, developed in our labs to a collection of publicly available, as well as generated in house, short- and long-reads sequencing experiments in different healthy and pre-clinical models.

Rationale: We have recently shown that epigenetic remodelling enzymes, such as HDAC inhibitors, are feasible drugs in HNC. Preliminary data are indicating some deregulated epigenetics marks suggesting the corresponding histone modifiers as possible targets for the treatment of HNC, providing an attractive and feasible option to build upon.  Our overarching hypothesis is that unique histone marks distinguish HPV+ and HPV- HNC and that specific histone modifiers are novel mediators of HNC tumorigenesis in an HPV specific manner.
Experimental design: Samples (HNC patients' tissues and body fluids) have been/will be collected and characterized using a broad spectrum of OMICs and other assays.
i) Mass-spectometry analysis. By mass spec approaches and ELISA assays histone modifications will be analyzed in a global manner to detect cell/patient-specific differences in potentially regulatory hPTMs and regulators.
ii) Transcriptome analysis. By RNA-seq we will examine the transcriptional landscape of patient-derived tumor cells to identify active and repressed genes.
iii) ChIP-seq analysis. To link histone modifications to gene expression profiles genome-wide histone modifications will be determined by ChIP-seq in HNC cells.
iv) Inhibitors and knockout/knockdown. Functional links between global and local changes will be established by genetic or pharmacological inhibition of histone modifying enzymes in HNC cells and patients' derived organoids.

The research will be based on the identification of the mechanisms underlying heart failure. In particular, the candidate will carry out research aimed at defining the phenotype of a humanised model of LMNA mutation causing cardiomyopathy and on gene editing studies aimed at normalising the phenotype through a Crisp/Cas9 approach. Other projects are available according to the CV of the candidate

Thyroid hormones are essential iodinated molecules produced by the thyroid gland and essential for the metabolism and growth of all vertebrates. In humans, thyroid hormone levels are finely tuned across life and development, and their unbalance is related to cancer, hypothyroidism, and autoimmune diseases.
What are the molecular determinants of thyroid hormone regulation?
The successful PhD candidate will reveal how thyroglobulin, the thyroid hormone precursor, orchestrates the hormone balance with its many partners. How? Using an integrative structural biology approach, ranging from in vitro biochemical and biophysical assays, cryo-EM analysis and structural proteomics, including crosslinking-mass spectrometry. The in vitro models built with high-resolution methods during the PhD project will be then tested in cells and potentially in organoid models. This study is essential to open new avenues towards the regulation of thyroid hormones in health and disease.
For more details on Francesca Coscia’s group and funding, please visit:
https://humantechnopole.it/en/research-groups/coscia-group/
https://erc.europa.eu/news/erc-starting-grants-2021-project-highlights

Replication forks are constantly challenged by exogenous and endogenous threats inducing replication stress (RS), which has been linked to cell transformation. RS is monitored by DNA repair proteins, including tumor suppressors BRCA1/2. Unresolved RS and consequent DNA damage induce cell fate changes typical of tumors, as we have recently demonstrated (Elife 2020). Using biochemical and cancer cell-based assays, combined with DNA electron-microscopy, we discovered that BRCA1/2 prevent replicative DNA gaps and DNA degradation, the products of which induce innate immunity responses. Malfunction of BRCA1/2 activates low fidelity repair pathways that fuel genome instability, promoting cancer cell chemo-resistance. Among these, we have shown that POLQ-dependent ones prevent replication fork breakage. Inhibition of POLQ is a promising strategy to kill chemo-resistant cancer cells by synthetic lethality. Over the years our work has been published in several high impact papers in which PhD students figure as first authors (Mol Cell 2017, 2018, 2021 and 2022, Elife 2020 and Nature 2018).
The incoming PhD student(s) will work on one of these topics through multidisciplinary approaches, including protein/DNA biochemistry, proteomic analysis, DNA electron-microscopy, advanced imaging, CRISPR/Cas9-based genetics and chromatin/RNA bioinformatics using as models purified proteins, cell-free extracts, patient-derived cancer cells, stem cells, and embryos.

We recently reported that SARS-CoV2 infection leads to DNA damage generation, cellular senescence and inflammation (Gioia, Tavella et al Nature Cell Biology 2023). We now aim too pursue the following two distinct, but mutually supportive, research lines.
1. What is the impact of altered NTP levels on DNA replication and genome stability? What is the structure of the DNA replication forks in these infected cells? What is the extent of the mutations induced? Which are the preferential genomic sites of DNA damage accumulation? Is telomere biology affected? Is the inflammatory response linked to the above events?
2. Genome instability is a feature of cancer. What is the impact of SARSCOV2 infection, or the expression of individual viral genes on the genome maintenance mechanisms, including those known to be tumor suppressive functions? Our preliminary results already identified altered pathways that are key in preventing cancer and modulating response to therapy. 

The candidate will be part of an international team and will be supported by a number of established experimental systems, technologies and range of collaborators to rapidly advance along the above-described research cell lines.

The human brain, formed by millions of diverse cells, is the most complex organ known. How these cells collectively mediate brain function and behavior and why they lead to dysfunction in disease is not understood. We will combine single-cell multi omic data analysis, comparative genomics, and mechanistic modeling to study brain cell behavior in evolution, development, and disease. Computational predictions will guide collaborative experiments to dissect the mechanistic basis and behavioral consequences of brain (dys)function, opening up opportunities for therapeutic intervention and control.

Cancer is a dynamic disease. Oncogenesis and tumor progression require the integrated destabilization of several key cellular regulatory processes. This phenomenon creates the necessary substrate for heterogeneity, which is subsequently maintained by selective pressures, including immune and therapeutic pressures. Cancer heterogeneity might result in a non-uniform distribution of genetically distinct cancer-cell subpopulations across and within disease sites (spatial heterogeneity) or temporal variations in the molecular makeup of cancer cells (temporal heterogeneity). Cancer heterogeneity underlies site-specific responses, provides the seeds for the emergence of resistance and disease relapse, and also complicates the selection of globally effective therapeutic agents. Therefore, an accurate assessment of tumor heterogeneity is essential for the development of effective therapies. So far, efforts in understanding cancer heterogeneity were largely limited to cancer cells. These revealed a remarkably complex and diverse portrait of cancer cells, with evidence for genetic diversification and clonal selection. However, the complex ecosystem of stromal cells, infiltrating immune cells, endothelial cells that, together with non-cellular tissue components, constitute the tumor microenvironment (TME), are themselves as complex and heterogeneous as the cancer cell compartment. Indeed, the high-level complexity of the TME is accompanied by substantial heterogeneity at the intra-tumoral, inter-tumoral, and inter-individual levels. Therefore, a comprehensive characterization of the whole tumor ecosystem is increasingly recognized to hold the promise for improving the benefit of anticancer (immune)therapies. 
So far, bulk-based omic analyses provided insights into the functional mechanisms in the TME, yet providing only a “global” view of TME, averaging out underlying differences in cell-type specific transcriptomes, while obscuring the presence of cells with low abundance and highly specialized functions. At odds, single-cell RNA-sequencing (scRNAseq) enables specific profiling of cell populations at the single-cell level and decodes single-cell intercellular signaling networks, thus rendering each individual cell type unique. This unbiased, innovative, characterization renders scRNAseq a mainstream technique in cancer research as it provides clear insights into the entire tumor ecosystem, such as mechanisms of intratumoral and intertumoral heterogeneity, as well as cell–cell interactions and offers a clear snapshot of the precise state of every single cell, reflecting its functional role, history, and stochastic fluctuations. Therefore, scRNA-seq measurements in combination with computational analysis can reveal the transcriptional basis for heterogeneous cell states.
In this study, we are intended to provide a single-cell TME atlas for different solid tumors, both primary and metastatic lesions in multiple tumor types by multiregion, single-cell sequencing of samples at diagnosis, surgery (ideally, pre- and post-therapy), and eventually at autopsy, from patients and murine mouse models. By analyzing scRNAseq data from TME and matching them with non-malignant tissue, we will try to decipher TME heterogeneity as well as the dynamics of tumor evolution and adaptation to natural and therapy-induced (immune)pressures. Indeed, single-cell technology provides the sensitivity needed to screen for the emergence of therapy-resistant clones and exhausted and/or dysfunctional immune infiltrating cells. This would potentially allow tailored treatment early in the course of relapse and minimize ongoing tumor-host co-evolution associated with treatment resistance.
Hence, in providing a comprehensive “catalog” of TME cell types, their functional status and co-optive interactions, this study can serve as a valuable resource and a proof-of-concept to identify biomarkers and targets and enable more informed personally tailored (on the timing and the modality) therapeutic decisions for patients with malignant tumors.

Our research is focused on the discovery of novel treatment strategies in difficult-to-treat hematologic malignancies such as Acute Leukemias and Aggressive Lymphomas.

The main field of interest is the study of chemoresistant lymphoma and leukemia specific vulnerabilities for the implementation of novel therapies based on synthetic lethalities.

We are especially interested in targeting synthetic lethalities in MYC-driven aggressive lymphomas and TP53 mutant leukemias, focusing on MYC, BCL-2, MCL-1, DNA repair and telomere dysfunction. On the other hand, we are implementing novel strategies to enhance the efficacy of current immunotherapies including chimeric antigen receptor (CAR) T and NK-cell therapy.

For these aims we employ preclinical leukemia and lymphoma models, large scale multi-omics profiling and we interrogate publicly available annotated clinical datasets.

The main goal of our lab is the rapid transition of preclinical findings in precision-therapy clinical trials. Another goal of our research is the identification of biomarkers allowing response prediction, which could useful for better selection of patients for precision-therapy approaches.

Sometimes fragments of our genome can form extrachromosomal circular DNA (eccDNA). These species accumulate in tumor cells where they promote intratumor heterogeneity and evolution. Despite their relevance, still little is known on the mechanisms of eccDNA biogenesis. We have found that eccDNA formation at telomeres and other tandem repeats is triggered by DNA damage, which induces the formation of DNA loops that can then be excised as extrachromosomal circles. 
The aim of this project will be to identify genetic pathways that affect the formation of DNA loops at telomeres and other tandem repeats and their excision as eccDNA. To this end, the candidate will use state of the art molecular biology and imaging techniques, combined with CRISPR-based genetics to identify factors that prevent or stimulate formation of damage-induced DNA loops. Targets selection will be supported by a proteomic analysis of telomeres with and without induction of DNA loops. Finally, the candidate will be involved in a high-throughput sequencing project, aimed at identifying regions prone to eccDNA formation upon DNA damage.
If successfully completed, this project will help define the genetic basis of eccDNA accumulation in tumor cells.

Immune development is essential for human life as demonstrated by the fatal consequences of inborn errors of immunity. Exposure to pathogens, vaccines and other environmental antigens during childhood shape our immune system. These exposures lead to lasting effects, most notably, to the differentiation, expansion and maintenance of memory lymphocytes. Despite the key importance of these events, our knowledge of the dynamic characteristics of the human developing immune system remains limited.
As part of this project, the PhD candidate will dissect the paediatric immune cell landscape and the influence of individual genetic backgrounds on cellular phenotypes. In the Domínguez Conde laboratory we apply the single-cell genomics toolbox to decipher the developmental trajectories of immune cells. Specifically, we perform deep cellular phenotyping using scRNA-seq with paired scVDJ-seq, CITE-seq and scATAC-seq. We apply these techniques in both uni- and multimodal setups. The integration of these orthogonal molecular readouts at the single-cell level will be the cornerstone of this project. The candidate will develop a data analysis pipeline that will allow the integration, annotation and identification of phenotypes associated with specific developmental stages.
This position would ideally suit a candidate who is passionate for developmental immunology and computational biology.

We have recently created a pipeline for imaging large samples by cryo-electron tomography using an improved lift-out procedure. We now seek to apply this technology to understanding the power and the limitation of investigating liquid liquid phase separation of proteins relevant to neurodegenerative disorders in vitro, in cells, and in tissue.

Glioblastoma (GBM) are very aggressive tumors (14 months of life expectancy after diagnosis). They are non-curable because GBM cells are highly proliferative and exceedingly invasive, migrating on linear tracks like the abluminal walls of brain blood vessels. Glioblastoma transcriptomic and genomic analysis showed high inter- and intra-patient heterogeneity. We also showed high inter-patient heterogeneity in GBM motility modes and linked them to their mechanoproperties. We proved the value of gridded micropatterns as a mimicry of peri-vascular migration. At this stage, we want to investigate more deeply GBM heterogeneity in motility modes, mechanoproperties and molecular signatures at single patient level.
The PhD position will be aimed at decorticate the functions of major molecular players in GBM mechanobiology and motility. The student should be interested in biophysical approaches (force measurement in cells, microfabrication…) highly driven by microscopic observations. A bioengineer profile with high interest in leaning more biology will be a good match. Interdisciplinary profiles are encouraged and welcome. The expected results of motility analysis coupled with mechanical and molecular signatures will serve as milestones to study intra-patient diversity in glioblastoma.

Recent relevant contributions of the lab: Monzo et al. Dev Cell 2021, Ghisleni et al. Nature Com 2020, Barger et al. Nature com 2019.

Acute Myeloid Leukaemia (AML) is a rare disease in children and teenagers but a significant cause of childhood cancer mortality. Relapse is the primary cause of treatment failure. Outcomes have not improved over the last two decades and novel therapies are therefore urgently needed. The successful treatment AML has been hindered by the disease heterogeneity and complicated by the chemo-resistant and immune-evasive properties of AML leukaemia stem cells (LSCs). LSCs persist in a dormant state which limits their uptake of cytotoxic drugs and makes them selectively unresponsive to conventional chemotherapies. As a consequence, quiescent LSCs undergo a selective survival advantage during treatment and can eventually fuel disease relapse. Intrinsic properties of AML cells can lead to the accumulation of suppressive immune cell populations and impaired cytotoxic lymphocytes activity. In turn, an impaired immune system, can promote AML disease progression. Decoding how the crosstalk between LSCs and their immune microenvironment evolves across stages of the disease, promises to unravel intrinsic and extrinsic mechanisms of resistance and pinpoint a therapeutic windows therapeutic intervention. 
This project will combine multiomic single cell technologies with stem cell and immune functional assays, to reconstruct LSCs trajectories of disease evolution and identify therapeutic vulnerabilities for targeted intervention.

We will focus on the development of novel computational tools and machine learning methods to identify drug repositioning opportunities for rescuing or preventing SARS-CoV-2-related neuropathologies.
This project will be conducted within the Horizon Funded NeuroCOV consortium activities, using publicly available chemogenomic databases and unprecedented longitudinal transcriptomic data generated by collaborators in the consortium.

The DNA damage response (DDR) and immune response are two pivotal processes in the development and progression of cancer, characterized by intricate molecular mechanisms that remain poorly understood. The DDR pathways are essential for maintaining genomic stability and preventing the onset of cancer. Simultaneously, the immune system plays a crucial role in identifying and eradicating cancerous cells, and disruptions in immune surveillance are associated with tumor progression. Interestingly, inhibiting DDR pathways can enhance the immunogenicity of cancer cells, rendering them more vulnerable to immune attacks, thereby transforming "cold" tumors into "hot" tumors. Designing and using novel computational methods, we will aim to elucidate the interplay between DDR and the immune response by leveraging publicly available cancer genomics databases integrated with recently assembled data from chemo/functional-genetic screens. Our ultimate goal will be to investigate how this can be utilised to develop effective combination therapies.

This is a collaborative project with (and externally funded by) Nerviano Medical Sciences (NSM). The enrolled PhD student will focus on developing computational and machine learning methods to elucidate the crosstalk between DNA damage and immune responses. This will involve the analysis of publicly available genomics and functional genetics datasets, as well as experimental data generated in house.

Background
Several factors play a role in cancer progression and response to radiotherapy. A heterogeneous tumor microenvironment, the varying patient characteristics, as well as the radiotherapy schedule and timing of administration complicate the dynamic relationship between radiotherapy and this immune landscape. With the development of high-precision radiotherapy, the identification of patients who will be benefits from tailored radiotherapy schedules and techniques (including both particle therapy and photons) in combination with immunotherapy is becoming a crucial unmet topic.

Aim
This project aims to build a predictive model able of choosing the best therapeutic strategy considering the individual patient and tumour features.

Methods
1. Systematic review of in vitro/clinical studies identifying factors and investigating patterns of radioresistance/radiosensitivity
2. Retrospective cohort study addressing patient and tumour features associated with patterns of failure or benefit of radiotherapy; machine learning approaches will be used for building a model including text (clinical records), medical imaging, histopathologic and genomics data for predicting radioresistance/radiosensitivity; empirical data collected in clinical practice of IEO radiotherapy division as well as those identified from systematic review (please see point 1) will be integrated in the model
3. Real data cohort study aimed to apply the identified algorithm in order to validate the model
 

Background:
The integration of cutting-edge technologies and advanced treatment modalities in clinical and radiation oncology, such as proton therapy, immunotherapy, and state-of-the-art imaging techniques, has ushered in a new era of high-throughput data sources that can potentially be incorporated into patients' diagnostic and therapeutic workup.
Despite the potential benefits, the massive scale and complexity of these data sources pose significant challenges and, as a result, there is a pressing need to develop novel approaches that exploit them to improve patient outcomes and optimize treatment processes.

Aim:
The primary objective of this project is to leverage large-scale patient data by also employing -omics sciences, mainly radiomics and dosiomics, to identify predictive biomarkers and develop models for evaluating patient outcomes. 

Methods: 
1. Retrospective cohort study to mine data for the development of machine-learning models for outcome prediction.  
2. Workflows analysis to identify inefficiencies and flaws in treatment processes and test the adherence to state-of-the-art references by process mining.
3. Development of frameworks to enable clinicians to personalize treatments for their patients and achieve better outcomes through the use of tailored treatment strategies. 

Across animals, the key to generate complex body plans from a single cell resides in the capacity to generate asymmetries early in development, by establishing spatially distinct gene expression territories. To reproduce and study these events in a reductionist manner, we work with new organoid models of neurodevelopment where precise genetic control (e.g. by synthetic biology and optogenetics) enables to reconstitute in vitro complex signalling events such as morphogen gradients.
By using microscopy, single-cell RNA-seq and spatial transcriptomics data, the candidate will try to understand the principles guiding the emergence of spatial gene expression territories in neurodevelopment, and will then probe their hypotheses for example by genetic perturbations and additional functional genomics approaches.

Neurons are highly polarized cells which function by forming functional connections with each other and with other cells. They possess the unique ability of changing the nature and number of these connections (synaptic plasticity), which strongly depends on their capacity to tightly regulate gene expression at different levels, from transcription to turnover, subcellular localization of RNA and translation (transcriptome plasticity). Recently, transcriptomic technologies made a huge leap in terms of throughput and resolution: we can now measure transcription and turnover rates genome-wide, map protein-RNA interactions at nucleotide resolution, accurately quantify translation and polyadenylation and image hundreds of transcripts in parallel at submicron resolution.
Within this project, the candidate will tackle neuronal transcription plasticity by integrating cutting-edge transcriptomic modalities, such as short and long-read RNA sequencing, spatial transcriptomics, Ribo-seq, CLIP and metabolic labelling, in order to build quantitative models of mRNA metabolism in human neurons, upon different stimuli and genetic perturbations.

FAM46C is one of the most frequently mutated genes in Multiple Myeloma (MM) and its mutations are associated with poor prognosis (1,2,3).
Our lab has demonstrated that in MM cells FAM46C acts in complex with the FNDC3A protein and works as an oncosuppressor by orchestrating intracellular trafficking and protein secretion(4). 
Recently, FAM46C was proposed to have an active function also in other cancer types(5), and, accordingly, evidence in our hands pinpoints to a role for FAM46C also in breast cancer.
The aim of this PhD project is to define the oncosuppressor role of the FAM46C/FNDC3A complex in the breast cancer environment by employing biochemical, molecular, cellular and single cell biology state-of-the-art techniques. In so doing, we plan to define which pathways are modulated/altered by expression of a functional FAM46C/FNDC3A complex and determine their targetability. Results in this direction will be fundamental for improving knowledge about breast cancer and for implementing therapeutic strategies.
References:
1) Chapman, M. A. et al. 2011, doi:10.1038/nature09837.
2) Bolli, N. et al. 2014, doi:10.1038/ncomms3997.                
3) Lohr, J. G. et al. 2014, doi:10.1016/j.ccr.2013.12.015.
4) Manfrini,  N., Mancino, M. et al. 2020, doi: 10.1158/0008-5472.CAN-20-1357. 
5) Deng J, Xiao W, Wang Z. 2022, doi: 10.3389/fgene.2022.81025.

The PhD project will address the molecular mechanisms of Wnt-dependent self-renewal in the regulation of stem cell activity, tissue homeostasis and oncogenesis, with emphasis on intestinal cancers. Colorectal cancer is a leading cause of death among industrialized nations. A major issue affecting treatment efficacy is the high relapse rate, which largely depends on the presence of deregulated cancer stem-like cells. The normal adult intestinal epithelium is a polarized monolayer constantly being renewed by intestinal stem cells residing at the base of invaginations called crypts, whose proliferation is governed by Wnt3-ligands secreted by Paneth cells acting as niche. Wnt-signalling leads to beta-catenin stabilization and transcriptional activity. Evidence from our lab revealed that upon Wnt3 stimulation the protein NuMA is found in complexes with beta-catenin and participate to Wnt response.
The PhD project aims at characterizing the organizational principles of Wnt-dependent NuMA-containing complexes and to explore their functions with a combination of integrative structural biology (cryo-EM), biochemistry, cell biology in artificial niches and organoids, as well as multi-omics. These studies will shed light on the mechanistics of Wnt self-renewal, likely paving the way to novel therapeutic strategies to treat intestinal cancers.

We have recently demonstrated that the tumor suppressor NF1, widely investigated as a RAS repressor, participates in multiple RAS-independent functions and is associated with selective response to antibody-drug conjugates in HER2+ breast cancer. To further our understanding of NF1 biology and druggability, we will develop mouse models of somatically inactivated NF1 tumors using cre-lox technology and CRISPR. We will employ single cell RNA sequencing and multidimensional imaging to investigate NF1 role in metastasis, cytoskeletal dynamics and the tumor immune environment.

The altered epigenome shapes the behavior of tumor cells, imposing transcriptional programs driving progression and resistance to current anti-cancer therapies. Environmental changes represent a key driver of epigenetic changes, and tumor cell metabolism/signaling pathways regulated by nutrient availability affect the epigenome through different mechanisms. 
We have found that signaling mediated by the PP2A holo-complex is regulated by nutrient availability, and that the activation of specific PP2A forms by impairing critical cellular bioenergetic pathways can be exploited therapeutically in preclinical models of cancer. More recently, we have found that in some tumor subtypes this phenomenon is accompanied by differential association of PP2A with the epigenome, which we aim in the PhD project to explore mechanistically, and to translate in novel approaches to cancer treatment.

Despite significant lymphocyte infiltration, responses to immune checkpoint inhibitors (ICI) are still heterogenous and largely restricted to a fraction of tumors. Seminal works from us and others have pointed at the microbiome as master regulator of ICI response and its therapeutic value has been recently confirmed by two independent clinical trials. In this propject we will test if therapeutic manipulation of the metabolic output of gut bacteria can improve the response of solid tumors to ICI.

Our scientific goal is to provide key insights into regulatory mechanisms that involves non-coding RNAs (short and long transcripts) and control gene expression at the transcriptional, post-transcriptional or epigenetic level. This goal will be achieved through the application of advanced genomics technologies, developed for the discovery of RNA-based molecular mechanisms. A key priority is identifying among all non-coding RNAs and DNA elements, those that can play a functional role in promoting cancer aggressive behaviors, which can be used as disease markers or potential targets for pharmacological intervention. Our approaches incorporate the most recent high-resolution technologies, including single-cell multi-omics and Nanopore single molecule sequencing, used to dissect tumor heterogeneity at the phenotypic and transcriptional level, and CRISPR-based genetic approaches (cas9-/cas13-, CRISPRi and CRISPRa) exploited at individual gene level and at group level for functional screenings (CRISPR-library, CROP-seq approaches). In order to investigate non-coding RNA biology also at preclinical level, we take advantage of cancer models established in the years and available through our clinical cancer network, including cancer cell lines, primary samples, primary cultures and 3D models, such as patient-derived xenografts (PDX) and organoids (PDOs).

Hosting Lab: The Genomic-Science Lab consists of 12 people (1 technologist, 1 technician, 5 post docs, 4 PhD students, 1 research fellows) plus other affiliated senior researchers. The lab is part of a vibrant international scientific network of IIT, centered on RNA biology, which includes the RNA initiative (iRNA@IIT); the LONGTREC consortium (European Doctoral-Network) focused on long-read sequencing, the National Center for Gene Therapy and Drugs based on RNA Technology, and many collaborators form outstanding international research institutes, including the EMBL-EBI; the RIKEN Institute; Karolinska Institutet.

Links

https://www.iit.it/web/irna

New immunotherapeutic approaches aim at restoring the natural balance and increase immune response against cancer by different mechanisms. The heterogeneity of immune cell subpopulations and their complex interactions, though, represent a real challenge when trying to develop novel immunotherapies and evaluate or predict their efficacy in vivo. In our lab we are focusing on the immunosuppressive T cell compartment that promotes tumor growth by dampening specific antitumor immune responses. Toward a better understanding of the molecular basis underlying tumor regulatory T cells function, we generated a comprehensive epigenetic profile (by ChIPseq and ATAC-seq) of peripheral blood, normal tissue and tumor infiltrating Treg cells (tiTreg). Among regulatory elements we focused on enhancers that are key to coordinate gene expression programs in a tissue-specific manner. Assessment of transcription factor binding dynamics to these regions showed transcription factors with distinct binding activity profile across Treg populations that are clearly lost or gained specifically in tiTreg suggesting the presence of regulatory hubs underlying the acquisition of their specific identity at tumor sites. With this proposal we aim to provide insights on these regulatory hubs through the modulation of selected target by standard shRNA downmodulation or CRISPR/Cas9 based editing approaches towards specific reprogramming of regulatory T cells recruited at tumor sites. Moreover, to investigate the basis of tumor immune-suppression, we will leverage a human tumor explant model which incorporates both epithelial and stromal components into a collagen-based air liquid interface 3D culture system. This model recapitulates the physiology of the whole tumor microenvironment (TME) maintaining tumor cells with the associated immune populations for days in culture, allowing for modulation of potentially actionable targets and the concurrent assessment of the interplay among the different components of the TME by combined methodologies such as multiparametric flow cytometry (FACS) analysis and single-cell transcriptome sequencing.

Establishing and maintaining cellular identities involves multiple signals that instruct the activity of transcription factors and chromatin-remodeling activities to define cellular transcriptional states. These mechanisms play crucial roles in human pathologies and are directly implicated in the development of cancer. Indeed, deregulation of chromatin remodeling activities are frequent causative events. 

The Polycomb machinery represents the major repressive system in facultative heterochromatin and plays a crucial role in organism development and differentiation. The machinery is composed by more than 50 distinct factors forming multiple ensembles with high biochemical and functional heterogeneity to sustain the complexity of transcriptional identities. Indeed, mutations of several of these factors are common driver events in human tumor making this machinery a major oncogenic player and a very attractive target for cancer therapy.

The projects will be aimed at decrypting such functional complexity combining approaches of genetic engineering with integrative and multi-omics approaches to uncover molecular vulnerabilities that could pave the way to new cancer prevention and treatment strategies.

Pelicci's group current activities mainly focus on the characterization of intra-tumoral genetic and phenotypic heterogeneity as critical drivers of disease progression and therapy resistance through the exploitation of multi-omic approaches, reverse genetics, cutting-edge preclinical models and patient samples. The final goal is to identify novel targeted treatments.
The PhD candidate will be offered one of the projects outlined below.
1) Leukemia. Based on robust preliminary results, we will develop novel treatment approaches based on the targeting of: a) NPM1c+, the most frequent AML mutation. We will investigate chromatin compartmentalization of methionine metabolism and mechanisms of NPMc+ antagonism and obtain pre-clinical evidence of clinical efficacy using available or new drug formulations of our lead candidate. b) Chemoresistance.  We will test whether chemoresistance can be prevented by interfering with DNA methylation or reactivating specific stress pathways in quiescent LSCs. c) Quiescence. We will investigate mechanisms of blast quiescence induction and the role of quiescence in preventing stress-induced apoptosis and immune clearance of AML blasts.
2) Breast Cancer. Leveraging transcriptional lineage tracing, we will dissect the genetic and phenotypic heterogeneity of breast cancer chemoresistance, investigating clonal dynamics and transcriptional changes of resistant clones, from the primary tumor to distant organs.

Intra-tumoral genetic and phenotypic heterogeneity is a constant trait of the transformed phenotype and thought to be critical for tumor growth, metastatization and drug resistance.
We have developed a novel multi-omics platform, called SCM-seq (Single-Cell-Molecule-sequencing), which combines short-read scRNA-seq with long-read Nanopore sequencing of full-length barcoded cDNA and allows mapping at single cell level of transcriptional profiles, expressed mutations, transcript isoforms and T-cell receptor (TCR) profiles. We are applying these technologies to the analysis of metastasis formation in breast cancer and the emergence of drug resistance in breast cancer and leukemia, using mouse models (syngenic and PDX) of human tumors. In parallel, we are setting up prospective lineage tracing approaches in patients, combining  mitochondrial DNA mutations and scRNAseq.
More detailed description of the ongoing projects in Pelicci's lab can be found in the project outline for the molecular-oncology PhD candidate.

Glioblastoma is the most aggressive and heterogeneous primary brain tumor with varying clinical presentation and poor prognosis.
Treatment failures are due to GBM inter- and intra-tumor cellular heterogeneity, disease infiltrative nature and clinical pitfalls. Stem-like cells, or Tumor Initiating Cells (TICs), at the apex of glioblastoma cell hierarchy are recognized as major contributor to glioblastoma heterogeneity and therapy resistance. These cells are highly tumorigenic and assumed to respond to anti-cancer molecules similarly to the matched human primary tumours. Thus, their eradication is an unmet clinical need.
We had begun to address this challenge in the context of TICs functional targets. In this regard, our most recent results demonstrate that a specific and brain penetrant LSD1 inhibitor exerts anti-tumor activity by counteracting TIC features. LSD1-directed therapy is effective only in a subset of glioblastoma. We are defining the molecular mechanisms of stemness therapeutic resistance as a feature dependent on metabolic plasticity. In our mind such plasticity protects TICs from stressful cues. We expect that the identification of specific metabolic vulnerabilities or the dependency on multiple energy-producing programs could be exploited to define pharmacologic approaches for TICs eradication. These approaches, in synergy with LSD1-directed therapy, may revolutionize the pre-clinical studies on glioblastoma.

RNA abundance and its variation arise from the combined action of transcriptional and post-transcriptional machineries responsible for the synthesis of novel transcripts, their processing into mature species, and the degradation of the latter, collectively setting the dynamics of the RNA life cycle. Epitranscriptional modifications, whose patterning is controlled by the action of writers and erasers and decoded by specific readers, are emerging as important determinants of RNA fate, impacting key biological processes in healthy and disease conditions. Yet, we still have a limited understanding on the consequences of the aberrant regulation of epitranscriptional modifications on specific steps of the RNA life cycle.
The PhD student will participate into the development of computational methods for determining the impact of various modifications on RNA fate, gaining training on Nanopore single molecule RNA sequencing, machine learning, mathematical modelling, epitranscriptomics and cancer biology. She/he will work in a Lab funded by AIRC - the Italian Foundation for Cancer Research - closely collaborating with IEO and IIT (https://www.iit.it/it/web/irna) groups. The student will benefit from a highly interdisciplinary environment where experienced computational and experimental postdocs lead highly integrated projects focused on the role of the epitranscriptome on RNA fate in cancer development, vulnerabilities and resistance.
The PhD student will be hosted in the Lab headed by Mattia Pelizzola and co-supervised with the Lab headed by Francesco Nicassio.

RNA editing by adenosine deamination is the most prominent epitranscriptome modification occurring in mammalian RNAs. It is carried out by ADAR enzymes acting on double RNA strands and its deregulation has been linked to several human disorders including immunological, neurological, neurodegenerative diseases and cancer. To date, over 15 million events from healthy human tissues have been identified and collected in the specialized REDIportal database. More than 95% of known edited sites reside in non-coding regions consisting of inversely oriented repetitive elements (mostly Alu elements). While the detection of RNA editing in non-coding regions is trivial, unveiling the complete landscape of recoding events, altering the encoded protein, is challenging but of course functionally relevant. Indeed, RNA editing represents a precious source of neoantigens and may play a relevant function in shaping the alternative splicing repertoire.
The aim of this proposal is to develop novel and effective computational methods to detect RNA editing based neoantigens including also those generated from individual-specific alternative splicing in large cohorts of cancer RNAseq data. The wealth of generated data will be used to enlarge the current REDIportal collection.

Cilia ate ubiquitous organelles, found in most cells, tissues and organs of the human body. Defects of the ciliary structure causes numerous human pathologies, called ciliopathies. We will use cell biology (Crispr targeted mutagenesis, immunofluorescence expansion microscopy, single molecule fluorescence microscopy, etc.) and structural biology methods (in situ cryo-electron tomography, subtomogram averaging, structural proteomics, etc.) to investigate machineries required for the assembly and maintenance of cilia.

Ecological and evolutionary processes of microbial pathogens are key to understanding antibiotic resistance and human health. Antibiotic treatment is a complex interplay of antibiotic chemistry, bacterial physiology, and ecology. Increasing evidence indicates that antibiotic resistance evolution cannot be decoupled from bacterial physiology and environmental conditions. In real-life situations, bacteria are rarely in isolation and often grow in the presence of other microbes and/or environmental conditions that are not constant. How can we predict antibiotic resistance evolution in such cases? 

In this project, we will interrogate the evolution of antibiotic resistance in complex scenarios, including changing environments and interactions between members in simple microbial communities. We will combine theory and experiments to develop computable models of drug action grounded on cell metabolism models and mechanistic models of evolutionary response for antibiotics targeting different cellular processes (e.g., translation, transcription, cell-wall inhibitors). By informing rational protocols for sustainable antibiotic use, methods developed in this program will help the fight against the growing and alarming problem of antibiotic resistance.

The HECT E3 ubiquitin ligase NEDD4 plays a crucial role in regulating the stability and trafficking of plasma membrane receptors and signaling proteins. Previous research from our lab identified a Ub exosite in HECT as essential for enzyme processivity, and we have developed selective inhibitors to confirm our model.
Currently, we are investigating the contribution of N-terminal domains to catalysis and using Cryo-EM, mutagenesis, and time-resolved FRET-based assays to study the key determinants of K63 specificity and chain elongation. These ongoing structural studies aim to provide a better understanding of NEDD4's function and facilitate the development of targeted therapies for related diseases.

 Tumor-specific alternative splicing (AS) events have been found to play a crucial role in cancer cell adaptation during tumorigenesis. Recent evidence from the lab suggests that beta-catenin has a significant impact on AS reprogramming during colorectal cancer (CRC) onset and progression, independent of its role in transcription. We are currently dissecting the molecular mechanism exploited by beta-catenin, using a combination of RNA seq/ RIP analysis, advanced imaging techniques, genetic and biochemical tools. In-depth molecular characterization of selected cancer-specific isoforms and their validation in cancer settings can aid in identifying novel molecular biomarkers during cancer progression or even new candidate targets. Indeed, AS can be therapeutically targeted by restoring the expression of non-oncogenic isoforms using antisense oligonucleotides (AONs), as we are currently doing for myosin VI.

We are seeking for a highly motivated PhD candidate to join a European doctoral program focused on the study of decision-making processes, usability experience, utility, and trust in AI-driven clinical decision-making in cancer patients and healthcare professionals. 
To ensure an optimal implementation of AI in clinical practice, it is of paramount importance to take into consideration the patients’ and healthcare professionals’ attitudes, beliefs and, other than the specific needs. Specifically, the way the individuals mentally represent a problem guides judgment and decision making. 
The PhD candidate will be part of the Applied Research Division for Cognitive and Psychological Science, currently consisting of researchers, post-doc fellows, PhD candidates, and clinical psychologists. The Division is affiliated to the Department of Oncology and Hemato-Oncology of the University of Milan (UNIMI). The department has extensive research collaboration, both internally and with other research environments nationally and internationally.

The successful PhD candidate will be involved in the following activities: 
o Conduct research in the field of General and Health Psychology;
o Contribute to the development and optimization of protocols;
o Analyze and interpret data and present findings at the group meeting and conferences;
o Write and publish scientific articles in international journals.

We are seeking for a highly motivated PhD candidate to join a European doctoral program focused on the study of patients’ and health professionals’ shared decision-making processes during the cancer trajectory.
Decision making is a complex multifactorial non-linear process. Personal knowledge,  individual differences and emotions, and contextual factors affect choices and shared decision making in health care. Studies should investigate further potential moderators of shared decision making and its implementation in clinical practice, also with the support of new technologies such as eHealth and virtual reality.  
The PhD candidate will be part of the Applied Research Division for Cognitive and Psychological Science, currently consisting of researchers, post-doc fellows, PhD candidates, and clinical psychologists. The Division is affiliated to the Department of Oncology and Hemato-Oncology of the University of Milan (UNIMI). The department has extensive research collaboration, both internally and with other research environments nationally and internationally.

The successful PhD candidate will be involved in the following activities: 
o Conduct research in the field of General and Health Psychology;
o Contribute to the development and optimization of protocols;
o Analyze and interpret data and present findings at the group meeting and conferences;
o Write and publish scientific articles in international journals.
 

Our laboratory investigates how epigenetic mechanisms regulate basic cell function and how their dysregulation favors cancer development, with a particular focus on chromatin-based mechanisms. By combining experimental and computational approaches, we seek to understand: (i) the epigenetic basis of malignant cell phenotypes at various disease stages; (ii) associated vulnerabilities that can be exploited to interfere with the disease. 
In this project, we aim to understand how mutations in chromatin modifiers, which are widely selected across all cancer types, impact the cellular response to oncogenes. Using the histone acetyl-transferase p300 as a paradigm, we will employ CRISPR-based Saturation Genome Editing (Findlay et al. Nature 2018) to model thousands of single-nucleotide substitutions detected across cancer types. Many of these variants appear to be under positive selection in patients, but their functional impact has been unclear. We will generate libraries of cells engineered to express individual variants from the endogenous locus, and use parallel functional assays that select mutations affecting - in various combinations - gene expression, histone marks, genome integrity and cellular fitness in normal or oncogene-challenged cells. Characterization of selected mutants will finally employ a combination of genomics (e.g. bulk and single-cell RNA-seq, ATAC-seq, ChIP-seq), quantitative microscopy and in vivo assays.

Our laboratory investigates how epigenetic mechanisms regulate basic cell function and how their dysregulation favors cancer development, with a particular focus on chromatin-based mechanisms. By combining experimental and computational approaches, we seek to understand: (i) the epigenetic basis of malignant cell phenotypes at various disease stages; (ii) associated vulnerabilities that can be exploited to interfere with the disease. 
Targeting of diverse classes of epigenetic regulators has shown efficacy in various cancer types and limited toxicity in normal tissues. However, the response of cancer cells to epigenetic drugs is highly variable, showing poor correlation with genetic background. In this project, we will use various computational strategies to examine how cumulative disruption of epigenetic regulation in cancer cells creates synthetic lethal vulnerabilities. By combining analysis of publicly available and ad-hoc generated datasets (bulk and single-cell RNAseq, Exome-seq, and drug sensitivity data) with artificial intelligence approaches (machine learning and artificial neural networks) we will identify features that predict sensitivity to epigenetic drugs. A particular focus will be on combined alterations in distinct classes of epigenetic regulators (e.g. chromatin remodellers, histone modifiers, histone variants, etc.) that destabilize the epigenetic regulatory network. A solid expertise in programming and previous experience with relevant approaches is required.

The process in which locally confined epithelial malignancies progressively evolve to become invasive cancer cells is associated with the acquisition of cell motility, fostered by a tissue-level phase transition (PT) from a solid-like to a liquid-like state, known as unjamming. The biomolecular machinery behind unjamming and its pathophysiological relevance have only begun to be unraveled. We have shown how the dynamic changes associated with PT feature the coexistence of long-range coordinated motion and local cell re-arrangement and are sufficient to promote matrix remodeling, and local invasion and exert mechanical stress on individual cell nuclei. This is accompanied by profound transcriptional rewiring, with the unexpected activation of an inflammatory response, change in cell state, and the emergence of malignant traits. Noticeably, carcinoma is composed of a heterogeneous set of cells that differ not only in their genetic landscape but also in their mechano-phenotypes. The impact of mechano-heterogeneity on tissue-level jamming transition is poorly understood. Here, we will also discuss unpublished findings that suggest that contact percolation, a purely geometrical feature, can impact the collective migratory behavior of tissues and, strikingly, promote the activation of an inflammatory gene transcription program in normal and breast carcinoma models.

Cells are often depicted as irregular spherical objects - the shape they adopt in suspension. However, the packed environment of tissues alters this simple shape, causing large cell deformations. This occurs during normal tissue growth and is even more pronounced upon tissue overgrowth, as in the case of solid tumors. We have observed that changes in the shape of cells and organelle(s) induce reversible and irreversible modifications in their behaviour and function(s). We hypothesize that cells use such mechanisms to integrate the successive deformations of distinct amplitudes and durations that they experience during their lifetime.
To address this question in the context of 3D tumor masses, we aim to create a set of devices and experiments that enable us to examine bulk cluster deformability and how this mechanical perturbation influences collective cell events, such as sorting, motility and invasion and further impact on tumor fate by influencing the transcription and epigenetic landscape.

The research activity is part of the project ERC-CoG microTOUCH to study person-to-person microbiome transmission (MT) and how MT shapes the microbiome in the context of non-communicable diseases.
To verify the hypothesis of microTOUCH, the research program can be focused on either experimental cultivation-based approaches targeting specific transmissible members of the human microbiome or on the development of computational tools to perform large-scale meta-analysis of metagenomic data.

The project aims at investigating the microbiological basis of fecal microbiota transplantation and its associated clinical outcome.
The successful candidate will work on large-scale shotgun metagenomics data produced by an ongoing international initiative and will integrate the data with other available datasets. Validation in experimental models will also be performed.

It has become recently possible to profile the molecular content of human cells at unprecedented resolution. Those multidimensional datasets from single cells are highly complex and hard to interpret in a biologically meaningful way. In our lab, we generate single cell multi-omic readouts from oncological patients and patient-derived model systems to study cancer progression and the emergence of treatment resistance. To be transformative for cancer medicine, single-cell multiomic requires cutting edge data analysis, as well as the development of novel machine learning algorithms for data integration that will allow extracting new biological and medical information.
In this project we aim at develop and implement new methods and approaches for the analysis and interpretation, in light of tumour evolution, of single cell data generated in our lab.

We study the dynamics of synapse formation in human and apes using iPSC-derived induced neurons. The PhD candidate will unravel the cell biological basis and functional consequences of the different synaptogenesis tempo.

We are a cell biology lab that studies how single neural stem cell identity influences brain development, focusing on intracellular traffic and protein glycosylation. Thanks to a collaboration with clinicians, we recently started working on Congenital Disorders of Glycosylation (CDGs), a class of rare diseases associated with neurological manifestations. By using brain organoids and induced neurons the PhD candidate will model CDGs in a dish to gain insight into the role of protein glycosylation in physiology and in neurodevelopmental disorders.

GTF2I is a transcription factor involved in the pathogenesis/progression of several rare cancers, including thymic epithelial tumours (TETs), the most frequent adult mediastinal cancer, that poses a significant challenge in terms of patient’s care. TETs are caused mainly by a recurrent hotspot GTF2I driver mutation, known as p.L383H/L424H, found in up to 49% of patients. This specific mutation renders GTF2I unrecognisable by the proteasomal degradation machinery, due to the alteration of a noncanonical destruction box, and has been proven oncogenic in murine thymic epithelial cells (TECs). 
Through a high-throughput small-molecule screening, we identified Histone Deacetylases Inhibitors (HDACi) as a promising treatment for GTF2I-associated diseases. In particular, we found that vorinostat causes a significant GTF2I downregulation at RNA and protein levels. Similarly, recurrent evidence indicates that small molecule inhibitors of the GTF2I co-factor Lysine-specific Demethylase 1 (LSD1i) ablate GTF2I pathogenic effects.
The successful candidate will thus elucidate the role of epigenetic modifiers along the GTF2i axis in TETs, investigating the mechanisms underpinning the activity of HDACi and LSD1i and evaluating the safety and efficacy of such treatments in close-to-patient in vitro models, such as thymic neoplastic organoids.

Long-term neurological and neuropsychiatric complications of infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) accompany as many as one third of COVID-19 cases, with a major impact on individual and societal welfare. While neurological deficits and psychiatric complications are increasingly recognized in patients with COVID-19, symptoms are diverse, difficult to predict, and little is known about which central nervous system (CNS) cell types or neuronal subpopulations are permissive to infection by SARS-CoV-2 or affected by SARS-CoV-2 associated inflammation and/or immunological responses.
Within a European HORIZON funded consortium, this PhD project aims at defining the cellular and molecular mechanisms that ground the spectrum of personalized NeuroCOVID disease trajectories in terms of the host-virus interactions, dissecting the direct and the indirect (i.e. immune/inflammatory) components of resilience and vulnerability. It will entail the analysis of the genetic risk factors that underlie NeuroCOVID and the elucidation, at single cell multiOMIC resolution, of the molecular pathways that mediate cognitive and neurodegenerative phenotypes through uniquely informative cohorts of primary samples isogenically matched to advanced organoid models of the respective CNS target areas. 
The selected PhD student will study the factors specific to neuronal and glial subpopulations that are critical for viral control and for protection against its immune and/or inflammatory-mediated damage through computation analysis of single cell omics and spatial transcriptomics datasets generated from primary samples and patients’ induced pluripotent stem cells derived brain organoids. 
The study of cell to cell interactions will be key to creating a computational workflow that explains in vivo phenotypes, with a major reach for neuroimmunology and beyond.

Endocrine disrupting chemicals (EDCs) are a widespread and hazardous class of substances that interfere with hormonal signaling causing a wide range of adverse health effects. The interplay of their impact with the diversity of human genetic backgrounds and predispositions remains however to be elucidated. 
In this context our lab spearheaded the first interdisciplinary and systematic dissection of the molecular impact of the mixture of EDCs associated to language delay in a pregnancy cohort, integrating the epidemiological data with brain organoids modelling (Caporale et al., Science, 2022). 
The RE-MEND Horizon research project aims now at identifying risk and protective factors for mental health and illness during critical life phases where endocrine signalling is crucial for shaping the neural substrate of individuals’ mental states. It will integrate data from longitudinal cohort studies with experimental neurobiology to establish mechanistic understanding of associations observed in epidemiology. 
Our group harnesses brain organoids as a transformative model to study the molecular basis of gene-environment interactions in the context of EDC exposure during sensitive windows of neurodevelopment.
In this project the PhD student will leverage human pluripotent stem cell lines reprogramming, (epi)genome engineering and cortical brain organoids to mechanistically elucidate the impact of a wide range of EDCs on multiple genetic backgrounds. 

Endocrine disrupting chemicals (EDCs) are a widespread and hazardous class of substances that interfere with hormonal signalling causing a wide range of adverse health effects. The interplay of their impact with the diversity of human genetic backgrounds and predispositions remains however to be elucidated. 
In this context our lab spearheaded the first interdisciplinary and systematic dissection of the molecular impact of the mixture of EDCs associated to language delay in a pregnancy cohort, integrating the epidemiological data with brain organoids modelling (Caporale et al., Science, 2022). 
The RE-MEND Horizon research project aims at identifying risk and protective factors for mental health and illness during critical life phases where endocrine signalling is crucial for shaping individual’s mental state. It will integrate data from longitudinal cohort studies with experimental neurobiology to establish mechanistic understanding of associations observed in epidemiology. 
Our group harnesses brain organoids as a transformative model to study the molecular basis of gene-environment interactions in the context of EDC exposure during sensitive windows of neurodevelopment.
In this project the PhD student will carry out advanced computational analysis of the EDC-induced alterations of the molecular circuitries by single cell and spatial omics, as well as integrating experimental data with human cohorts’ clinical and exposure metadata and omics biomarkers.

Genome structure and organisation is largely controlled by the activity of loop extruder complexes (SMC complexes) throughtout the cell cycle. Integrating different structural biology approaches (cryo-EM, single molecule studies and cross-link mass spectrometry) we aim to obtain a mechanistical understanding of this process and the paramount role of SMC complexes in genome folding and their association with auxiliary proteins to control chromosome compaction, such as transcription factors, topoisomerases, chromokinesins and chromatin remodellers.

The actual research projects will be identified among the research lines offered at TIGEM. Check the website for details:

https://www.tigem.it/research/research-faculty

The actual research projects will be identified among the research lines offered at CEINGE. Check the website for details:

https://www.ceinge.unina.it/en/faculty-list

Colorectal cancers (CRC) often display chromosomal instability (CIN). CIN originates from pre-mitotic defects, including DNA replication stress (RS), or mitotic defects, including a dysfunctional mitotic checkpoint (SAC). The precise contribution of these defects to intratumoral heterogeneity (ITH) and whether they impact on antitumor immune response require further investigation.
We previously demonstrated that CRC patient-derived cells frequently display DNA replication errors and a weak SAC. Preliminary evidence also suggests an impact of RS and mitotic stress (MS) on therapy resistance and immunogenicity. Based on this evidence, we hypothesize that RS and SAC deregulation can activate a specific intracellular stress response (i) fostering ITH, (ii) driving therapy resistance, and (iii) leading to the emission of immunomodulatory signals. To dissect this response, we will perform multi-omic studies (including single-cells) on primary cells or PDX subjected to specific strategies of RS or MS induction that we have already identified. Our aim is to identify (i) patterns of clonal selection upon therapies, (ii) biomarkers predicting drug response, (iii) mechanisms of resistance, (iv) modulated targets/pathways, and (v) immune-related parameters, including immunomodulatory factors. In vitro and in vivo validation of these targets/factors will drive the development of novel (immuno)therapeutic strategies against CRC.

In this project the candidate will develop automated pipelines to analyse and extract novel biomarkers from sequencing data. The candidate will learn to use tools such as NextFlow to build reproducible and scalable data analysis and integration pipelines. In addition, the candidate will learn to apply machine learning tools to extract biomarkers from multi-dimensional genomics and transcriptomics data.
The project is done in collaboration with other groups at IEO and abroad.