In pancreatic cancer patients, chemotherapy reshapes the gene expression profile and antigen receptor repertoire of T lymphocytes and enhances their effector response to tumor-associated antigens.

Introduction: Pancreatic Ductal Adenocarcinoma (PDA) is one of the most aggressive malignancies with a 5-year survival rate of 13%. Less than 20% of patients have a resectable tumor at diagnosis due to the lack of distinctive symptoms and reliable biomarkers. PDA is resistant to chemotherapy (CT) and understanding how to gain an anti-tumor effector response following stimulation is, therefore, critical for setting up an effective immunotherapy.

[Synchronies and asynchronies in the development of COVID-19 pandemic in Italy].

Background: the study of the possible determinants of the rise and fall of infections can be of great relevance, as was experienced during the COVID-19 pandemic. One of the methods to understand whether determinants are simultaneous or develop through contiguity between different areas is the study of the diagnostic replication index RDt among regions.

Objectives: to introduce the analysis of RDt variability and the subsequent application of a recently introduced functional clustering method as highly useful procedures for recognizing the presence of clusters with similar trends in epidemic curves.

Modulation of faecal miRNAs highlights the preventive effects of a Mediterranean low-inflammatory dietary intervention.

Background: Dietary interventions have been proposed as therapeutic approaches for several diseases, including cancer. A low-inflammatory Mediterranean dietary intervention, conducted as a pilot study in subjects with Familial Adenomatous Polyposis (FAP), reduced markers of local and systemic inflammation. We aim to determine whether this diet may modulate faecal microRNA (miRNA) and gene expression in the gut.

A single cell RNAseq benchmark experiment embedding "controlled" cancer heterogeneity.

Single-cell RNA sequencing (scRNA-seq) has emerged as a vital tool in tumour research, enabling the exploration of molecular complexities at the individual cell level. It offers new technical possibilities for advancing tumour research with the potential to yield significant breakthroughs. However, deciphering meaningful insights from scRNA-seq data poses challenges, particularly in cell annotation and tumour subpopulation identification.

Dietary intervention for tertiary prevention in head and neck squamous cell carcinoma survivors: clinical and translational results of a randomized phase II trial.

Background: There is a strong need for preventive approaches to reduce the incidence of recurrence, second cancers, and late toxicities in head and neck squamous cell carcinoma (HNSCC) survivors. We conducted a randomized controlled trial (RCT) to assess a dietary intervention as a non-expensive and non-toxic method of tertiary prevention in HNSCC survivors.

Methods: Eligible participants were disease-free patients with HNSCC in follow-up after curative treatments.

Tamoxifen Activates Transcription Factor EB and Triggers Protective Autophagy in Breast Cancer Cells by Inducing Lysosomal Calcium Release: A Gateway to the Onset of Endocrine Resistance.

Among the several mechanisms accounting for endocrine resistance in breast cancer, autophagy has emerged as an important player. Previous reports have evidenced that tamoxifen (Tam) induces autophagy and activates transcription factor EB (TFEB), which regulates the expression of genes controlling autophagy and lysosomal biogenesis. However, the mechanisms by which this occurs have not been elucidated as yet.

A new computational workflow to guide personalized drug therapy.

Objective: Computational models are at the forefront of the pursuit of personalized medicine thanks to their descriptive and predictive abilities. In the presence of complex and heterogeneous data, patient stratification is a prerequisite for effective precision medicine, since disease development is often driven by individual variability and unpredictable environmental events. Herein, we present GreatNectorworkflow as a valuable tool for (i) the analysis and clustering of patient-derived longitudinal data, and (ii) the simulation of the resulting model of patient-specific disease dynamics.

A Fecal MicroRNA Signature by Small RNA Sequencing Accurately Distinguishes Colorectal Cancers: Results From a Multicenter Study.

Background & Aims: Fecal tests currently used for colorectal cancer (CRC) screening show limited accuracy in detecting early tumors or precancerous lesions. In this respect, we comprehensively evaluated stool microRNA (miRNA) profiles as biomarkers for noninvasive CRC diagnosis.

Methods: A total of 1273 small RNA sequencing experiments were performed in multiple biospecimens.

CONNECTOR, fitting and clustering of longitudinal data to reveal a new risk stratification system.

Motivation: The transition from evaluating a single time point to examining the entire dynamic evolution of a system is possible only in the presence of the proper framework. The strong variability of dynamic evolution makes the definition of an explanatory procedure for data fitting and clustering challenging.

Results: We developed CONNECTOR, a data-driven framework able to analyze and inspect longitudinal data in a straightforward and revealing way.

Single-Cell RNAseq Complexity Reduction.

An important step in single-cell RNAseq data analysis is the preparation of the single cell transcription data for cell sub-population partitioning. In this chapter, we describe how to perform complexity reduction for 3' end single-cell RNAseq transcriptomics data.

Sparsely Connected Autoencoders: A Multi-Purpose Tool for Single Cell omics Analysis.

Background: Biological processes are based on complex networks of cells and molecules. Single cell multi-omics is a new tool aiming to provide new incites in the complex network of events controlling the functionality of the cell.

Methods: Since single cell technologies provide many sample measurements, they are the ideal environment for the application of Deep Learning and Machine Learning approaches.

Faecal miRNA profiles associated with age, sex, BMI, and lifestyle habits in healthy individuals.

For their stability and detectability faecal microRNAs represent promising molecules with potential clinical interest as non-invasive diagnostic and prognostic biomarkers. However, there is no evidence on how stool miRNA profiles change according to an individual's age, sex, and body mass index (BMI) or how lifestyle habits influence the expression levels of these molecules. We explored the relationship between the stool miRNA levels and common traits (sex, age, BMI, and menopausal status) or lifestyle habits (physical activity, smoking status, coffee, and alcohol consumption) as derived by a self-reported questionnaire, using small RNA-sequencing data of samples from 335 healthy subjects.

Stool microRNA profiles reflect different dietary and gut microbiome patterns in healthy individuals.

Objectives: MicroRNA (miRNA) profiles have been evaluated in several biospecimens in relation to common diseases for which diet may have a considerable impact. We aimed at characterising how specific diets are associated with the miRNome in stool of vegans, vegetarians and omnivores and how this is reflected in the gut microbial composition, as this is still poorly explored.

Design: We performed small RNA and shotgun metagenomic sequencing in faecal samples and dietary recording from 120 healthy volunteers, equally distributed for the different diets and matched for sex and age.

Application of the Euro Clonality next-generation sequencing-based marker screening approach to detect immunoglobulin heavy chain rearrangements in mantle cell lymphoma patients: first data from the Fondazione Italiana Linfomi MCL0208 trial.

Minimal residual disease (MRD) determined by classic polymerase chain reaction (PCR) methods is a powerful outcome predictor in mantle cell lymphoma (MCL). Nevertheless, some technical pitfalls can reduce the rate of of molecular markers. Therefore, we applied the EuroClonality-NGS IGH (next-generation sequencing immunoglobulin heavy chain) method (previously published in acute lymphoblastic leukaemia) to 20 MCL patients enrolled in an Italian phase III trial sponsored by Fondazione Italiana Linfomi.

MET Exon 14 Skipping: A Case Study for the Detection of Genetic Variants in Cancer Driver Genes by Deep Learning.

Background: Disruption of alternative splicing (AS) is frequently observed in cancer and might represent an important signature for tumor progression and therapy. Exon skipping (ES) represents one of the most frequent AS events, and in non-small cell lung cancer (NSCLC) MET exon 14 skipping was shown to be targetable.

Methods: We constructed neural networks (NN/CNN) specifically designed to detect MET exon 14 skipping events using RNAseq data.

Computational Analysis of Single-Cell RNA-Seq Data.

Single-cell RNAseq data can be generated using various technologies, spanning from isolation of cells by FACS sorting or droplet sequencing, to the use of frozen tissue sections retaining spatial information of cells in their morphological context. The analysis of single cell RNAseq data is mainly focused on the identification of cell subpopulations characterized by specific gene markers that can be used to purify the population of interest for further biological studies. This chapter describes the steps required for dataset clustering and markers detection using a droplet dataset and a spatial transcriptomics dataset.

Computational Analysis of circRNA Expression Data.

Analysis of circular RNA (circRNA) expression from RNA-Seq data can be performed with different algorithms and analysis pipelines, tools allowing the extraction of heterogeneous information on the expression of this novel class of RNAs. Computational pipelines were developed to facilitate the analysis of circRNA expression by leveraging different public tools in easy-to-use pipelines. This chapter describes the complete workflow for a computationally reproducible analysis of circRNA expression starting for a public RNA-Seq experiment.

Immune Trait Shifts in Association With Tobacco Smoking: A Study in Healthy Women.

Tobacco smoking is known to impact circulating levels of major immune cells populations, but its effect on specific immune cell subsets remains poorly understood. Here, using high-resolution data from 223 healthy women (25 current and 198 never smokers), we investigated the association between smoking status and 35,651 immune traits capturing immune cell subset frequencies. Our results confirmed that active tobacco smoking is associated with increased frequencies of circulating CD8+ T cells expressing the CD25 activation marker.

Sparsely-connected autoencoder (SCA) for single cell RNAseq data mining.

Single-cell RNA sequencing (scRNAseq) is an essential tool to investigate cellular heterogeneity. Thus, it would be of great interest being able to disclose biological information belonging to cell subpopulations, which can be defined by clustering analysis of scRNAseq data. In this manuscript, we report a tool that we developed for the functional mining of single cell clusters based on Sparsely-Connected Autoencoder (SCA).

Computational modeling of the immune response in multiple sclerosis using epimod framework.

Background: Multiple Sclerosis (MS) represents nowadays in Europe the leading cause of non-traumatic disabilities in young adults, with more than 700,000 EU cases. Although huge strides have been made over the years, MS etiology remains partially unknown. Furthermore, the presence of various endogenous and exogenous factors can greatly influence the immune response of different individuals, making it difficult to study and understand the disease.

The use of silicone wristbands to evaluate personal exposure to semi-volatile organic chemicals (SVOCs) in France and Italy.

In this exploratory study, we measured for the first-time human exposure to about 90 semi-volatile organic chemicals (SVOCs) in France and Italy using silicone wristbands. Participants in France (n = 40) and in Italy (n = 31) wore a silicone wristband for five days during 2018 and 2019. Samples were analyzed for 39 polybrominated diphenyl ethers (PBDEs), 10 novel brominated flame retardants (nBFRs), 25 organophosphate esters (OPEs), and 18 polycyclic aromatic hydrocarbons (PAHs).

In pancreatic cancer, chemotherapy increases antitumor responses to tumor-associated antigens and potentiates DNA vaccination.

Background: Pancreatic ductal adenocarcinoma (PDA) is an almost incurable tumor that is mostly resistant to chemotherapy (CT). Adaptive immune responses to tumor-associated antigens (TAA) have been reported, but immunotherapy (IT) clinical trials have not yet achieved any significant increase in survival, confirming the suppressive environment of PDA. As CT has immune-modulating properties, we investigated the effect of gemcitabine (GEM) in antitumor effector responses to TAA in patients with PDA.

Impacts of reopening strategies for COVID-19 epidemic: a modeling study in Piedmont region.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), the causative agent of the coronavirus disease 19 (COVID-19), is a highly transmittable virus. Since the first person-to-person transmission of SARS-CoV-2 was reported in Italy on February 21, 2020, the number of people infected with SARS-COV-2 increased rapidly, mainly in northern Italian regions, including Piedmont. A strict lockdown was imposed on March 21 until May 4 when a gradual relaxation of the restrictions started.

Small Nucleolar RNAs Determine Resistance to Doxorubicin in Human Osteosarcoma.

Doxorubicin (Dox) is one of the most important first-line drugs used in osteosarcoma therapy. Multiple and not fully clarified mechanisms, however, determine resistance to Dox. With the aim of identifying new markers associated with Dox-resistance, we found a global up-regulation of small nucleolar RNAs (snoRNAs) in human Dox-resistant osteosarcoma cells.

Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients.

Pancreatic Ductal Adenocarcinoma (PDA) is an aggressive malignancy with a very poor outcome. Although chemotherapy (CT) treatment has poor efficacy, it can enhance tumor immunogenicity. Tumor-Associated Antigens (TAA) are self-proteins that are overexpressed in tumors that may induce antibody production and can be PDA theranostic targets.