Multi-task deep latent spaces for cancer survival and drug sensitivity prediction.

MOTIVATION: Cancer is a very heterogeneous disease that can be difficult to treat without addressing the specific mechanisms driving tumour progression in a given patient. High-throughput screening and sequencing data from cancer cell-lines has driven many developments in drug development, however, there are important aspects crucial to precision medicine that are often overlooked, namely the inherent differences between tumours in patients and the cell-lines used to model them in vitro. Recent developments in transfer learning methods for patient and cell-line data have shown progress in translating results from cell-lines to individual patients in silico. However, transfer learning can be forceful and there is a risk that clinically relevant patterns in the omics profiles of patients are lost in the process. RESULTS: We present MODAE, a novel deep learning algorithm to integrate omics profiles from cell-lines and patients for the purposes of exploring precision medicine opportunities. MODAE implements patient survival prediction as an additional task in a drug-sensitivity transfer learning schema and aims to balance autoencoding, domain adaptation, drug-sensitivity prediction, and survival prediction objectives in order to better preserve the heterogeneity between patients that is relevant to survival. While burdened with these additional tasks, MODAE performed on par with baseline survival models, but struggled in the drug-sensitivity prediction task. Nevertheless, these preliminary results were promising and show that MODAE provides a novel AI-based method for prioritizing drug treatments for high-risk patients. AVAILABILITY AND IMPLEMENTATION: https://github.com/UEFBiomedicalInformaticsLab/MODAE.

Prevention of Meningococcal Disease: Knowledge, Attitudes, and Practices of General Practitioners and Primary Care Pediatricians in South Italy.

BACKGROUND: The purpose of this study was to evaluate the knowledge, attitude, and current practices about prevention of meningococcal disease among general practitioners (GPs) and primary care pediatricians (PCPs) in Italy. METHODS: A cross-sectional survey was carried out between February 2022 and July 2023 among a random sample of GPs and PCPs in Southern Italy. The data were collected using a questionnaire accessible via an internet link with the free software Google Forms®. RESULTS: Regarding the participants' knowledge toward meningococcal vaccinations, 84.2% of the PCPs and more than half of the GPs (55.2%) knew that the meningococcal B (MenB) vaccination is recommended for infants from the second month of life and 84.2% and 82.7% of the PCPs were aware that quadrivalent meningococcal ACWY (MenACWY) vaccine is recommended for children in the second year of life and adolescents, respectively. The GPs and PCPs considered vaccination against meningococcal disease to be very effective and safe with average values of 8.8 and 8.7, respectively, on a scale ranging from 1 to 10. Those with an older age, those who knew the medical conditions that expose patients to a higher risk of contracting meningococcal disease, and those who self-rated their knowledge on meningococcal disease as excellent/very good were more likely to consider the vaccination to be very effective and safe. Only 15.5% of the GPs and more than half of the PCPs (54.3%) administered anti-meningococcal vaccines to their patients. GPs and females were less likely to administer anti-meningococcal vaccines to their patients, whereas those who acquired information on meningococcal vaccinations by scientific journals were more likely to administer meningococcal vaccines. CONCLUSIONS: The findings of the survey highlighted the need of a greater engagement of GPs and PCPs in the immunization campaigns in order to increase meningococcal vaccination coverage.

Effectiveness and tolerability of givosiran for the management of acute hepatic porphyria: A monocenter real-life evaluation.

Acute hepatic porphyrias (AHPs) are a family of rare, autosomal, dominantly inherited conditions characterized by abnormalities in the production of heme. Advances in molecular engineering have provided new therapeutic possibilities for modifying the heme synthetic pathway in patients with porphyria. In particular, the RNA interference therapeutic givosiran was approved for the treatment of adults and adolescents with AHP aged >12 years based on the positive results of the phase III trial ENVISION. Despite the extended characterization of the activity of givosiran in clinical trials, reports on the long-term effects and effectiveness of the treatment in clinical practice are still scant. To fill this gap, this case series describes a monocentric Italian cohort of AHP patients treated with givosiran. Overall, our real-life experience supports the clinical evidence that long-term treatment with givosiran is well tolerated and able to provide sustained and continuous benefit to patients with acute intermittent porphyria, as reflected by the reduction in the frequency of attacks. In our series, givosiran treatment was also associated with improvement in assessments of quality of life, pain and fatigue.

Altered centriolar cohesion by CEP250 and appendages impact outcome of patients with pancreatic cancer.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the leading cause of cancer death worldwide. PDACs are characterized by centrosome aberrations, but whether centrosome-related genes influence patient outcomes has not been tested. METHODS: Publicly available RNA-sequencing data of patients diagnosed with PDAC were interrogated with unsupervised approaches to identify centrosome protein-encoding genes with prognostic relevance. Candidate genes were validated by immunohistochemistry and multiplex immunofluorescence in a set of clinical PDAC and normal pancreatic tissues. RESULTS: Results showed that two genes CEP250 and CEP170, involved in centrosome linker and centriolar subdistal appendages, were expressed at high levels in PDAC tissues and were correlated with prognosis of PDAC patients in independent databases. Large clustered γ-tubulin-labelled centrosomes were linked together by aberrant circular and planar-shaped CEP250 arrangements in CEP250-high expressing PDACs. Furthermore, PDACs displayed prominent centrosome separation and reduced CEP164-centrosomal labelling associated with acetylated-tubulin staining compared to normal pancreatic tissues. Interestingly, in a small validation cohort, CEP250-high expressing patients had shorter disease free- and overall-survival and almost none of those who received gemcitabine plus nab-paclitaxel first-line therapy achieved a clinical response. In contrast, weak CEP250 expression was associated with long-term survivors or responses to medical treatments. CONCLUSIONS: Alteration of the centriolar cohesion and appendages has effect on the survival of patients with PDAC.

AI identifies potent inducers of breast cancer stem cell differentiation based on adversarial learning from gene expression data.

Cancer stem cells (CSCs) are a subpopulation of cancer cells within tumors that exhibit stem-like properties and represent a potentially effective therapeutic target toward long-term remission by means of differentiation induction. By leveraging an artificial intelligence approach solely based on transcriptomics data, this study scored a large library of small molecules based on their predicted ability to induce differentiation in stem-like cells. In particular, a deep neural network model was trained using publicly available single-cell RNA-Seq data obtained from untreated human-induced pluripotent stem cells at various differentiation stages and subsequently utilized to screen drug-induced gene expression profiles from the Library of Integrated Network-based Cellular Signatures (LINCS) database. The challenge of adapting such different data domains was tackled by devising an adversarial learning approach that was able to effectively identify and remove domain-specific bias during the training phase. Experimental validation in MDA-MB-231 and MCF7 cells demonstrated the efficacy of five out of six tested molecules among those scored highest by the model. In particular, the efficacy of triptolide, OTS-167, quinacrine, granisetron and A-443654 offer a potential avenue for targeted therapies against breast CSCs.

Seroprevalence of measles antibodies in the Italian general population in 2019-2020.

In Italy, the measles elimination target has not yet been reached despite a significant reduction in cases. A multicenter study was conducted to estimate the prevalence of anti-measles (MV) IgG antibodies in the Italian population by age, sex and geographical area. To determine the level of MV-specific antibodies in sera, the immunoenzymatic assay ELISA was used (Enzygnost Anti-VZV/IgG, Siemens Healthcare Diagnostic Products GmbH, Germany). Overall, 3746 serum samples collected in the years 2019-20 from healthy subjects aged 6-64 years residing in 13 Italian regions. The overall seroprevalence of anti-MV IgG was 91.2 % (90.6 % male, 91.7 % female). Significantly higher seroprevalence values (p < 0.05) were recorded for the extreme age groups of the study population (6-9 years: 94.2 %; 40-64 years: 97.6 %). Subjects 20-39 and 40-64 years old had significantly higher antibody titers suggesting a protection against measles mainly derived from natural infection. Seroprevalence was significantly higher in the South (93.2 %) than in the Northern-Central Italy (88.9 %). The results indicate an increase in the overall seroprevalence data compared to previous investigations. However, further efforts must be made to implement and maintain high measles vaccination coverage to avoid the risk of future epidemic outbreaks.

Sudden Cardiac Death in the Young: State-of-the-Art Review in Molecular Autopsy.

Sudden cardiac death (SCD) is defined as unexpected death due to a cardiac cause that occurs rapidly. Despite the identification of prevention strategies, SCD remains a serious public health problem worldwide, accounting for 15-20% of all deaths, and is therefore a challenge for modern medicine, especially when it affects young people. Sudden cardiac death in young people affects the population aged ≤ 35 years, including athletes and non-athletes, and it is due to various hereditary and non-hereditary causes. After an autopsy, if the cause remains unknown, it is called sudden unexplained death, often attributable to genetic causes. In these cases, molecular autopsy-post-mortem genetic testing-is essential to facilitate diagnostic and therapeutic pathways and/or the monitoring of family members of the cases. This review aims to elaborate on cardiac disorders marked by genetic mutations, necessitating the post-mortem genetic investigation of the deceased for an accurate diagnosis in order to facilitate informed genetic counseling and to implement preventive strategies for family members of the cases.

Identification of therapeutic targets in osteoarthritis by combining heterogeneous transcriptional datasets, drug-induced expression profiles, and known drug-target interactions.

BACKGROUND: Osteoarthritis (OA) is a multifactorial, hypertrophic, and degenerative condition involving the whole joint and affecting a high percentage of middle-aged people. It is due to a combination of factors, although the pivotal mechanisms underlying the disease are still obscure. Moreover, current treatments are still poorly effective, and patients experience a painful and degenerative disease course. METHODS: We used an integrative approach that led us to extract a consensus signature from a meta-analysis of three different OA cohorts. We performed a network-based drug prioritization to detect the most relevant drugs targeting these genes and validated in vitro the most promising candidates. We also proposed a risk score based on a minimal set of genes to predict the OA clinical stage from RNA-Seq data. RESULTS: We derived a consensus signature of 44 genes that we validated on an independent dataset. Using network analysis, we identified Resveratrol, Tenoxicam, Benzbromarone, Pirinixic Acid, and Mesalazine as putative drugs of interest for therapeutics in OA for anti-inflammatory properties. We also derived a list of seven gene-targets validated with functional RT-qPCR assays, confirming the in silico predictions. Finally, we identified a predictive subset of genes composed of DNER, TNFSF11, THBS3, LOXL3, TSPAN2, DYSF, ASPN and HTRA1 to compute the patient's risk score. We validated this risk score on an independent dataset with a high AUC (0.875) and compared it with the same approach computed using the entire consensus signature (AUC 0.922). CONCLUSIONS: The consensus signature highlights crucial mechanisms for disease progression. Moreover, these genes were associated with several candidate drugs that could represent potential innovative therapeutics. Furthermore, the patient's risk scores can be used in clinical settings.

Genital and Oral HPV Geno-Prevalence Measured through Urine and Saliva Samples in Young Adults in Italy.

BACKGROUND: The aims of the study were to determine, in the urine and oral samples of young adults, the genotype-specific prevalence of Human Papilloma Virus (HPV) infection, the HPV DNA type-specific prevalence in unvaccinated and vaccinated individuals, and the determinants of HPV infection. METHODS: Selected participants were asked to fill in a self-administered questionnaire and to self-collect urine and saliva samples. RESULTS: Among the 1002 participants, 81 (8.1%) resulted positive for HPV DNA. The most common low-risk genotype was HPV 42 (2.2%), followed by HPV 43 (0.8%), and 40 (0.5%). The HPV 51 was the most common high-risk genotype (1.5%) followed by HPV 66 (1%) and HPV 68 (1%), and no participants were infected with HPV genotypes 18, 33, 45. Females, those who have had one or more occasional sexual partner, those who never/rarely/sometimes used condoms during their sexual activity, those with a previous diagnosis of sexually transmitted infection, and those who were not vaccinated were more likely to be tested positive for HPV infection. CONCLUSIONS: The low prevalence of genital HPV infections has provided evidence of the effectiveness of HPV vaccination both in vaccinated and not yet vaccinated subjects through herd immunity and indicated its decisive role in the changing epidemiology of circulating HPV genotypes in the population.

Proteomic signature profiling in the cortex of dairy cattle unravels the physiology of brain aging.

Introduction: Aging is a physiological process occurring in all living organisms. It is characterized by a progressive deterioration of the physiological and cognitive functions of the organism, accompanied by a gradual impairment of mechanisms involved in the regulation of tissue and organ homeostasis, thus exacerbating the risk of developing pathologies, including cancer and neurodegenerative disorders. Methods: In the present work, for the first time, the influence of aging has been investigated in the brain cortex of the Podolica cattle breed, through LC-MS/MS-based differential proteomics and the bioinformatic analysis approach (data are available via ProteomeXchange with identifier PXD044108), with the aim of identifying potential aging or longevity markers, also associated with a specific lifestyle. Results and discussion: We found a significant down-regulation of proteins involved in cellular respiration, dendric spine development, synaptic vesicle transport, and myelination. On the other hand, together with a reduction of the neurofilament light chain, we observed an up-regulation of both GFAP and vimentin in the aged samples. In conclusion, our data pave the way for a better understanding of molecular mechanisms underlying brain aging in grazing cattle, which could allow strategies to be developed that are aimed at improving animal welfare and husbandry practices of dairy cattle from intensive livestock.