Muscular dystrophies are a heterogeneous group of genetic disorders associated with an aberrant inflammatory response, that contributes to disease progression impairing regeneration and inducing fibrosis. Sarcoglycanopathies are recessively inherited limb-girdle muscular dystrophies (LGMDRs), in which the role of inflammation and its association with disease severity remains poorly understood, particularly in alpha-sarcoglycanopathy (LGMDR3). This study characterizes skeletal muscle and peripheral inflammatory signatures in 16 LGMDR3 patients and 8 unaffected individuals through bulk RNA sequencing with additional validation in Sgca-null mice. Patients were classified into mild and severe groups based on alpha sarcoglycan (SGCA) expression in muscle biopsy. Peripheral immunophenotype was assessed via flow cytometry analysis of peripheral blood mononuclear cells (PBMC). Principal component analysis showed a clear separation of severe LGMDR3 from mild LGMDR3 and unaffected individuals, with the latter two groups overlapping. Unsupervised hierarchical clustering analysis of the most variable genes identified distinct gene expression profiles between severe and mild LGMDR3 samples. Severe LGMD3 showed overexpression of innate immune system and T-cell activation pathways, with higher abundance of inflammatory infiltrate, mainly monocytes, cytotoxic T cells and dendritic cells. Notably, severe LGMDR3 were characterized by enrichment of M1-polarized macrophages and pro-inflammatory chemokines, whereas M2-polarized monocytes predominated in mild cases. Similar inflammatory profiles were observed in Sgca-null mice. PBMC analysis revealed significantly increased CD8+, TH1 CD4+ lymphocytes and activated monocytes in LGMDR3 patients compared with controls. Severe LGMDR3 patients additionally showed overexpression of genes governing fibrosis and muscle tissue regeneration and exhibited a clustering pattern similar to Duchenne muscular dystrophy patients. In conclusion, this study represents the first comprehensive characterization of LGMDR3 immunological profiles and demonstrated that inflammation plays a significant role in severe disease pathogenesis. The distinct immune signatures separating severe from mild cases provide a foundation for developing targeted anti-inflammatory therapies that may benefit severe LGMDR3 patients with severe phenotype.

Uveal melanoma (UM) is the most common intraocular tumor, and despite being rare, it accounts for nearly 13% of melanoma-related deaths. Indeed, patients with metastatic disease have typically survival rates of less than one year, with little improvement over the past few decades. Although TP53 mutations are uncommon in UM, recent findings highlight a dysfunctional p53 pathway in this cancer. Given its crucial role in mediating DNA damage responses, we analyzed the p53 protein functionality and downstream target activation in a panel of UM cell lines in response to standard-of-care treatments (i.e., cisplatin and proton-beam irradiation). Although most of the analyzed cells retained a wild-type p53, we observed a wide range of p53 protein stabilization and targets' activation. Recently, p53 isoforms have been recognized as modifiers of p53 activity, and their biology and functions depend on cellular context. We observed that UM cells express a broad spectrum of p53 isoforms, including Δ160p53α and Δ133p53β and the longer variants Δ40p53β and p53β. Interestingly, the down-regulation of the short p53 isoforms (Δ133/Δ160) revealed their contribution to promoting cell growth and in mitigating cell death triggered by standard-of-care therapies. Moreover, we verified the wild-type p53 status in a panel of 32 UM cases and analyzed the expression levels of p53 isoforms. Our results indicated a correlation between higher expression levels of Δ40p53α or Δ133p53γ isoforms and the development of more aggressive cancers. Our findings suggest that shorter p53 isoforms can promote cancer aggressiveness and therapy resistance, thereby providing crucial insights into UM pathogenesis.

Uveal melanoma (UM) is the most common primary intraocular malignancy with a limited five-year survival for metastatic patients. Limited therapeutic treatments are currently available for metastatic disease, even if the genomics of this tumor has been deeply studied using next-generation sequencing (NGS) and functional experiments. The profound knowledge of the molecular features that characterize this tumor has not led to the development of efficacious therapies, and the survival of metastatic patients has not changed for decades. Several bioinformatics methods have been applied to mine NGS tumor data in order to unveil tumor biology and detect possible molecular targets for new therapies. Each application can be single domain based while others are more focused on data integration from multiple genomics domains (as gene expression and methylation data). Examples of single domain approaches include differentially expressed gene (DEG) analysis on gene expression data with statistical methods such as SAM (significance analysis of microarray) or gene prioritization with complex algorithms such as deep learning. Data fusion or integration methods merge multiple domains of information to define new clusters of patients or to detect relevant genes, according to multiple NGS data. In this work, we compare different strategies to detect relevant genes for metastatic disease prediction in the TCGA uveal melanoma (UVM) dataset. Detected targets are validated with multi-gene score analysis on a larger UM microarray dataset.

Background The combination of Programmed Cell Death 1 (PD-1) and Cytotoxic T-Lymphocyte Antigen 4 (CTLA-4) blockade has dramatically improved the overall survival rate for malignant melanoma. Immune checkpoint blockers (ICBs) limit the tumor’s immune escape yet only for approximately a third of all tumors and, in most cases, for a limited amount of time. Several approaches to overcome resistance to ICBs are being investigated among which the addition of epigenetic drugs that are expected to act on both immune and tumor cells. Guadecitabine, a dinucleotide prodrug of a decitabine linked via phosphodiester bond to a guanosine, showed promising results in the phase-1 clinical trial, NIBIT-M4 (NCT02608437). Methods We used the syngeneic B16F10 murine melanoma model to study the effects of immune checkpoint blocking antibodies against CTLA-4 and PD-1 in combination, with and without the addition of Guadecitabine. We comprehensively characterized the tumor’s and the host’s responses under different treatments by flow cytometry, multiplex immunofluorescence and methylation analysis. Results In combination with ICBs, Guadecitabine significantly reduced subcutaneous tumor growth as well as metastases formation compared to ICBs and Guadecitabine treatment. In particular, Guadecitabine greatly enhanced the efficacy of combined ICBs by increasing effector memory CD8+ T cells, inducing effector NK cells in the spleen and reducing tumor infiltrating regulatory T cells and myeloid derived suppressor cells (MDSC), in the tumor microenvironment (TME). Guadecitabine in association with ICBs increased serum levels of IFN-γ and IFN-γ-induced chemokines with anti-angiogenic activity. Guadecitabine led to a general DNA-demethylation, in particular of sites of intermediate methylation levels. Conclusions These results indicate Guadecitabine as a promising epigenetic drug to be added to ICBs therapy.

T-cell acute lymphoblastic leukemia (T-ALL) is a hematologic tumor, characterized by several genetic alterations, that constitutes 15% of pediatric and 25% of adult ALL. While with current therapeutic protocols children and adults' overall survival (OS) rates reach 85-90% and 40-50%, respectively, the outcome for both pediatric and adult T-ALL patients that relapse or are refractory to induction therapy, remains extremely poor, achieving around 25% OS for both patient groups. About 60% of T-ALL patients show increased NOTCH1 activity, due to activating NOTCH1 mutations or alterations in its ubiquitin ligase FBXW7. NOTCH signaling has been shown to contribute to chemotherapy resistance in some tumor models. Hence, targeting the NOTCH1 signaling pathway may be an effective option to overcome relapsed and refractory T-ALL.Here, we focused on the therapeutic activity of the NOTCH1-specific monoclonal antibody OMP-52M51 in combination either with drugs used during the induction, consolidation, or maintenance phase in mice xenografts established from pediatric and adult relapsed NOTCH1 mutated T-ALL samples. Interestingly, from RNAseq data we observed that anti-NOTCH1 treatment in vivo affects the purine metabolic pathway. In agreement, both in vitro and in vivo, the greatest effect on leukemia growth reduction was achieved by anti-NOTCH1 therapy in combination with antimetabolite drugs. This result was further corroborated by the longer life span of mice treated with the anti-NOTCH1 in combination with antimetabolites, indicating a novel Notch-targeted therapeutic approach that could ameliorate pediatric and adult T-ALL patients outcome with relapse disease for whom so far, no other therapeutic options are available.

Background: Metastatic uveal melanoma (MUM) is a highly aggressive, therapy-resistant disease. Driver mutations in Gα-proteins GNAQ and GNA11 activate MAP-kinase and YAP/TAZ pathways of oncogenic signalling. MAP-kinase and MEK-inhibitors do not significantly block MUM progression, likely due to persisting YAP/TAZ signalling. Statins inhibit YAP/TAZ activation by blocking the mevalonate pathway, geranyl-geranylation, and subcellular localisation of the Rho-GTPase. We investigated drugs that affect the YAP/TAZ pathway, valproic acid, verteporfin and statins, in combination with MEK-inhibitor trametinib. Methods: We established IC50 values of the individual drugs and monitored the effects of their combinations in terms of proliferation. We selected trametinib and cerivastatin for evaluation of cell cycle and apoptosis. Synergism was detected using isobologram and Chou–Talalay analyses. The most synergistic combination was tested in vivo. Results: Synergistic concentrations of trametinib and cerivastatin induced a massive arrest of proliferation and cell cycle and enhanced apoptosis, particularly in the monosomic, BAP1-mutated UPMM3 cell line. The combined treatment reduced ERK and AKT phosphorylation, increased the inactive, cytoplasmatic form of YAP and significantly impaired the growth of UM cells with monosomy of chromosome 3 in NSG mice. Conclusion: Statins can potentiate the efficacy of MEK inhibitors in the therapy of UM.

Before a tumor is diagnosed and surgically removed, it has been growing for many months or even years [...]

The metastatic risk of uveal melanoma (UM) is defined by a limited number of molecular lesions, somatic mutations (SF3B1 and BAP1), and copy number alterations (CNA): monosomy of chromosome 3 (M3), chr8q gain (8q), chr6p gain (6p), yet the sequence of events is not clear. We analyzed data from three datasets (TCGA-UVM, GSE27831, GSE51880) with information regarding M3, 8q, 6p, SF3B1, and BAP1 status. We confirm that BAP1 mutations are always associated with M3 in high-risk patients. All other features (6p, 8q, M3, SF3B1 mutation) were present independently from each other. Chr8q gain was frequently associated with chr3 disomy. Hierarchical clustering of gene expression data of samples with different binary combinations of aggressivity factors shows that patients with 8q|M3, BAP1|M3 form one cluster enriched in samples that developed metastases. Patients with 6p combined with either 8q or SF3B1 are mainly represented in the other, low-risk cluster. Several gene expression events that show a non-significant association with outcome when considering single features become significant when analyzing combinations of risk features indicating additive action. The independence of risk factors is consistent with a random risk model of UM metastasis without an obligatory sequence.

Background and aim of the study: Mutations in the G alpha-genes GNAQ and GNA11 are found in 85-90% of uveal melanomas (UM). Aim of the study is to understand whether the mutations in both genes differentially affect tumor characteristics and outcome and if so, to identify potential mechanisms. Methods: We analyzed the association between GNAQ and GNA11 mutations with disease specific survival, gene expression profiles, and cytogenetic alterations in 219 UMs. We used tandem-affinity-purification, mass spectrometry and immunoprecipitation to identify protein interaction partners of the two G-proteins and analyzed their impact on DNA-methylation. Results: GNA11 mutation was associated with: i) an increased frequency of loss of BRCA1- associated protein 1 (BAP1) expression (p = 0.0005), ii) monosomy of chromosome 3 (p < 0.001), iii) amplification of chr8q (p = 0.038), iv) the combination of the latter two (p = 0.0002), and inversely with v) chr6p gain (p = 0.003). Our analysis also showed a shorter disease-specific survival of GNA11-mutated cases as compared to those carrying a GNAQ mutation (HR = 1.97 [95%CI 1.12-3.46], p = 0.02). GNAQ and GNA11 encoded G-proteins have different protein interaction partners. Specifically, the Tet Methylcytosine Dioxygenase 2 (TET2), a protein that is involved in DNA demethylation, physically interacts with the GNAQ protein but not with GNA11, as confirmed by immunoprecipitation analyses. High risk UM cases show a clearly different DNA-methylation pattern, suggesting that a different regulation of DNA methylation by the two G-proteins might convey a different risk of progression. Conclusions: GNA11 mutated uveal melanoma has worse prognosis and is associated with high risk cytogenetic, mutational and molecular tumor characteristics that might be determined at least in part by differential DNA-methylation. (C) 2022 Elsevier Ltd. All rights reserved.

Immune checkpoint inhibitors (ICIs) immunotherapy has represented a breakthrough in cancer treatment. Clinical use of ICIs has shown an acceptable safety profile and promising antitumor activity. Nevertheless, some patients do not obtain clinical benefits after ICIs therapy. In order to improve and cure an increasing number of patients, the field has moved toward the discovery of new ICIs expressed by cells of innate immunity with an elevated inherent antitumor activity, such as natural killer cells. This review will focus on the recent findings concerning the role of classical and non-classical immune checkpoint molecules and receptors that regulate natural killer cell function, as potential targets, and their future clinical application.

Scientific background: Environmental sampling of SARS-CoV-2 is a fundamental tool for evaluating the effectiveness of non-specific prophylaxis measures in counteracting virus spread. The purpose of our work was to evaluate the effectiveness of the different sampling methods in the hospital setting to assess their correlation with the structural, functional, and operational situation of the monitored departments and to define the dynamics of the spread of the virus in indoor environments.Methods: The monitoring (air bubbling sampling, surface wipe test) was carried out at the San Martino Polyclinic Hospital (Genoa, Italy) in the period since April 2020 to June 2021. The presence of viral RNA in the collected samples was evaluated by qPCR. The infection capacity of the samples collected was also evaluated by an in vitro challenge test on cells sensitive to SARS-CoV-2 infection.Results: The percentage of positivity with respect to the number of tests performed (sensitivity) were air bubbler 50%, wipe test 17%, and challenge test 11%. Only 20% of the samples tested positive in the wipe test and 43% of the samples tested positive in the bubbler sampling were also positive in the challenge test. All the positivity obtained was detected at a distance of less than 2 m and height of less than 1.5 from COVID-19 patients.Conclusions: Environmental contamination from SARS-CoV-2 detected at the San Martino Polyclinic Hospital is found lower than similar assessments performed in other hospitals both in Italy and abroad. Our study predicted that environmental monitoring of SARS-CoV-2 must be carried out in an integrated way by not using a single sampling method, as each individual test has a different biological significance and performance. However, the virus detected by wipe test only is often a degraded viral fragment and not an intact infecting virion.

Uveal melanoma (UM), a rare cancer of the eye, has been deeply characterized for its molecular lesions in terms of chromosomal copy number alterations (CNAs), gene expression, somatic mutations and DNA methylation (for reviews see [1, 2]). It shows a very limited number of somatic mutations, very few of which are recurrent [3] (probable initiator mutations in GNAQ [4], GNA11 [5], CYSLTR2 [6] and PLCB4 [7], all acting in the same G-protein coupled receptor signaling pathway, mutations in BAP1 [8] and SF3B1 [9] that drive metastasis and mutations in EIF1AX [10] that apparently are involved in tumor formation but not progression). A few CNAs (monosomy of chromosome 3 [11] chr8q gain [12] and chr6p gain [13]), global gene expression profiles or an expression analysis of a number of genes that have been included in a prognostic signature [14] as well as whole genome DNA methylation similarly distinguish two to four classes of UM [15]. It is possible to predict the propension to develop metastases based on each of these molecular domains. Approaches to fuse these data in order to develop a combined molecular predictor have not significantly improved prognostic assessment [16]. Our present knowledge on the mutational landscape of UM indicates that a single mutation in one of the four known “initiator” genes (GNAQ, GNA11, CYSLTR2, and PLCB4) is enough to form a tumor and a single further mutation in either BAP1 [8] or SF3B1 [9] is enough to drive metastasis. These mutations are almost perfectly segregated from the classes defined by gene expression profiling or by CNA. All these approaches yield two clearly distinct classes with each two subclasses with different metastatic potential. This clear distinction can be taken for evidence of non-continuous risk distribution, yet a recent single cell transcriptomics-based analysis hints at a mixture of class-1 low risk and class-2 high risk cells within a single tumor whereby the proportion of these two cell types finally determines the real risk of metastasis [17]. It is not clear how this cell admixture model can explain the clearly distinct risk-associated molecular classes and further research is needed to clear that point. The few driver mutations, even if assisted by secondary drivers [18], are best compatible with a linear tumor evolution model, but recent evidence introduced the punctuated equilibrium model (or the big bang model) to UM [19]. This model postulates a phase of high genomic instability followed by the outgrowth of stabilized clones into a heterogenous tumor [20, 21]. Tumor heterogeneity has not systematically been addressed for UM. Given the paucity of mutations, heterogeneous subpopulations are unlikely to be traceable by exome sequencing but CNA analyses might help. A recent large-scale analysis of CNA revealed much more cytogenetic events with a discrete frequency than heretofore believed [22]. Still we do not know the deletions of which genes on chromosome 3 except for BAP1 are important for UM metastasis. Early work trying to define the minimal critical interval could not single out specific genes [23]. Chr3 monosomy can come about in a single step by losing one copy during mitosis due to non-disjunction although cases with partial deletion of one copy of chr3 have been reported [24]. Alternatively, several genes including noncoding genes on chr3 can cooperate in determining the metastatic risk.