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Abstract Background ZAP-70 is an independent negative prognostic marker in chronic lymphocytic leukemia (CLL). Usually, its expression is investigated by flow cytometric protocols in which the percentage of ZAP-70 positive CLL cells is determined in respect to isotypic control (ISO-method) or residual ZAP-70 positive T cells (T-method). These methods, however, beside suffering of an inherent subjectivity in their application, may give discordant results in some cases. The aim of this study was to assess the prognostic significance of these methods in comparison with another in which ZAP-70 expression was evaluated as a Mean-Fluorescence-Intensity Ratio between gated T and CLL cells (T/B Ratio-method). Methods Cytometric files relative to ZAP-70 determination according to the three readouts were retrospectively reviewed on a cohort of 173 patients (test set), all with complete clinical and biological prognostic assessment and time-to-treatment (TTT) available. Findings were then validated in an independent cohort of 341 cases from a different institution (validation set). Results The optimal prognostic cut-offs for ZAP-70 expression were selected at 11% (ISO-method) or 20% of positive cells (T-method), as well as at 3.0 (T/B Ratio-method) in the test set; these cut-offs yielded 66, 60 and 73 ZAP-70+ cases, respectively. Univariate analyses resulted in a better separation of ZAP-70+ vs. ZAP-70- CLL patients utilizing the T/B Ratio, compared to T- or ISO-methods. In multivariate analyses which included the major clinical and biological prognostic markers for CLL, the prognostic impact of ZAP-70 appeared stronger when the T/B-Ratio method was applied. These findings were confirmed in the validation set, in which ZAP-70 expression, evaluated by the T- (cut-off = 20%) or T/B Ratio- (cut-off = 3.0) methods, yielded 180 or 127 ZAP-70+ cases, respectively. ZAP-70+ patients according to the T/B Ratio-method had shorter TTT, both if compared to ZAP-70- CLL, and to cases classified ZAP-70+ by the T-method only. Conclusions We suggest to evaluate ZAP-70 expression in routine settings using the T/B Ratio-method, given the operator and laboratory independent feature of this approach. We propose the 3.0 T/B Ratio value as optimal cut-off to discriminate ZAP-70+ (T/B Ratio less than 3.0) from ZAP-70- (T/B Ratio more/equal than 3.0) cases.

Abstract Studies of gene expression profiling have been successfully used for the identification of molecules to be employed as potential prognosticators. In analogy with gene expression profiling, we have recently proposed a novel method to identify the immunophenotypic signature of B-cell chronic lymphocytic leukemia subsets with different prognosis, named surface-antigen expression profiling. According to this approach, surface marker expression data can be analysed by data mining tools identical to those employed in gene expression profiling studies, including unsupervised and supervised algorithms, with the aim of identifying the immunophenotypic signature of B-cell chronic lymphocytic leukemia subsets with different prognosis. Here we provide an overview of the overall strategy employed for the development of such an "outcome class-predictor" based on surface-antigen expression signatures. In addition, we will also discuss how to transfer the obtained information into the routine clinical practice by providing a flow-chart indicating how to select the most relevant antigens and build-up a prognostic scoring system by weighing each antigen according to its predictive power. Although referred to B-cell chronic lymphocytic leukemia, the methodology discussed here can be also useful in the study of diseases other than B-cell chronic lymphocytic leukemia, when the purpose is to identify novel prognostic determinants.

Background: About 50% of cutaneous melanoma (CM) harbors the activating BRAFV600 mutation which exerts most of the oncogenic effects through the MAPK signaling pathway. In the last years, a number of MAPK modulators have been identified, including Spry1. In this context, we have recently demonstrated that knockout of Spry1 (Spry1KO) in BRAFV600-mutant CM led to cell cycle arrest and apoptosis, repressed cell proliferation in vitro, and reduced tumor growth in vivo. Despite these findings, however, the precise molecular mechanism linking Spry1 to BRAFV600-mutant CM remains to be elucidated. Materials and methods: Immunoprecipitation coupled to mass spectrometry was employed to gain insight into Spry1 interactome. Spry1 gene was knocked-out using the CRISPR strategy in the BRAF-mutant cell lines. Transmission electron microscopy was used to assess the relationship between Spry1 expression and mitochondrial morphology. By using in vitro and in vivo models, the effects of Spry1KO were investigated through RNA-sequencing, quantitative real-time PCR, Western blot, and immunofluorescence analyses. The Seahorse XF24 assay allowed real-time measurement of cellular metabolism in our model. Angiogenic potential was assessed through in vitro tube formation assays and in vivo CD31 staining. Results: Spry1 was mainly located in mitochondria in BRAFV600-mutant CM cells where it interacted with key molecules involved in mitochondrial homeostasis. Spry1 loss resulted in mitochondrial shape alterations and dysfunction, which associated with increased reactive oxygen species production. In agreement, we found that nuclear hypoxia-inducible factor-1 alpha (HIF1α) protein levels were reduced in Spry1KO clones both in vitro and in vivo along with the expression of its glycolysis related genes. Accordingly, Ingenuity Pathway Analysis identified "HIF1α Signaling" as the most significant molecular and cellular function affected by Spry1 silencing, whereas the glycolytic function was significantly impaired in Spry1 depleted BRAFV600-mutant CM cells. In addition, our results indicated that the expression of the vascular endothelial growth factor A was down-regulated following Spry1KO, possibly as a result of mitochondrial dysfunction. Consistently, we observed a substantial impairment of angiogenesis, as assessed by the tube formation assay in vitro and the immunofluorescence staining of CD31 in vivo. Conclusions: Altogether, these findings identify Spry1 as a potential regulator of mitochondrial homeostasis, and uncover a previously unrecognized role for Spry1 in regulating nuclear HIF1α expression and angiogenesis in BRAFV600-mutant CM. Significance: Spry1KO profoundly impacts on mitochondria homeostasis, while concomitantly impairing HIF1α-dependent glycolysis and reducing angiogenesis in BRAF-mutant CM cells, thus providing a potential therapeutic target to improve BRAFV600-mutant CM treatment. [ABSTRACT FROM AUTHOR]

Introduction: The functionalization of nanoparticles (NPs) with an antiCD19 targeting mechanism represents a promising approach for the selective delivery of drugs and nucleic acids into normal and tumor B cells. This strategy has the advantage of minimizing off-target effects by restricting gene delivery to the desired cell population. However, the nanoplatform must guarantee both the local production of the protein and the safety of the treatment to allow an effective therapy with reduced systemic toxicity. Methods: In order to ensure a selective delivery of nucleic acids, we developed poly(lactic-co-glycolic acid) (PLGA)-poly(vinyl alcohol) (PVA) NPs loaded with an Enhanced Green Fluorescent Protein (EGFP)-coding plasmid and covalently coated with antiCD19 recombinant antibody as a targeting mechanism. To assess the functionality of the NPs, physicochemical characterization, safety tests, and transfection assay were employed to evaluate the NPs' behavior in vitro and in vivo , in a human/zebrafish lymphoma xenograft model. Results: The results demonstrated that the PLGA-PVA nanoplatform was capable of efficiently encapsulating and releasing the payload. These nanostructures demonstrated a favorable safety profile, as evidenced by the absence of significant cell cytotoxicity, coagulation activation, complement system activation, and the slight activation of endothelial cells and leukocytes. The targeting mechanism facilitated the interaction of NPs with target cells, thereby enhancing their internalization and subsequent exogenous plasmid DNA (pDNA) translation and protein expression. In the human/zebrafish lymphoma xenograft model, no evidence of toxicity was observed, and targeted NPs demonstrated the capacity to enhance exogenous pDNA expression. Conclusion: Our findings provide a rationale for the use of targeted NPs as a DNA delivery system for the local expression of therapeutic proteins. [ABSTRACT FROM AUTHOR]

Background Drug delivery strategies using chitosan nanobubbles (CS-NBs) could be used to reduce drug side effects and improve outcomes in hepatocellular carcinoma (HCC) treatment. To enhance their action, a targeting agent, such as the humanized anti-GPC3 antibody GC33 (condrituzumab), could be attached to their surface. Here, we investigated the use of idarubicin-loaded CS-NBs for HCC treatment and a GC33-derived minibody (that we named 4A1) to enhance CS-NB delivery. Methods Various CS-NB formulations were prepared with or without 4A1 conjugation and idarubicin loading. Results CS-NBs had a positive charge and a diameter of about 360 nm. In in-vitro experiments using the HCC-like HUH7 cell line, CS-NBs showed a cytotoxic effect once loaded with idarubicin. In-vivo biodistribution in HUH7 tumor-bearing xenograft mice demonstrated that CS-NBs can accumulate in the tumor mass. This effect was enhanced by 4A1 conjugation (p = 0.0317). In HUH7 tumor-bearing xenograft mice, CS-NBs loaded with idarubicin and conjugated or not conjugated with 4A1 were both able to slow tumor growth, to increase mouse survival time compared to free idarubicin (p = 0.00044 and 0.0018, respectively) as well as to reduce drug side effects. Conclusions CS-NBs loaded with idarubicin can be a useful drug delivery strategy for HCC treatment. [ABSTRACT FROM AUTHOR]

Background Recently, we developed AT101, an IgM-class mouse monoclonal antibody directed against glypican-1 (GPC1), a proteoglycan that can be considered as useful target for glioblastoma multiforme (GBM) treatment being specifically and highly expressed on GBM cell surface. Here, we proposed the use of AT101 as targeting agent in a drug delivery nanoplatfom to effectively deliver chitosan nanobubbles (NBs) for GBM treatment. Methods Chitosan NBs were prepared and conjugated with AT101 or left unconjugated as control. Results The ability of AT101 to bind the GPC1 protein was demonstrated by flow cytometry and immunofluorescence analysis in the "GBM-like" GPC1-expressing cell lines U-87 MG and T98G. AT101 was shown to bind GPC1-expressing GBM tumor samples by immunofluorescence. In-vivo experiments in the U-87 MG xenograft model showed that AT101 was able to bind GPC1 on cell surface and accumulate in U-87 MG tumor masses (p = 0.0002 respect to control). Moreover, in-vivo experiments showed that AT101 is able to target GPC1 when conjugated to chitosan NBs, thus increasing their specific deliver to GPC1-expressing cells of U-87 MG tumor, as compared to chitosan NBs not conjugated to AT101 (p = 0.02). Conclusions AT101 is an useful targeting agent for the development of drug delivery nanoplatforms for GBM treatment. [ABSTRACT FROM AUTHOR]

Pharmacogenomics studies how genes influence a person's response to treatment. When complex phenotypes are influenced by multiple genetic variations with little effect, a single piece of genetic information is often insufficient to explain this variability. The application of machine learning (ML) in pharmacogenomics holds great potential — namely, it can be used to unravel complicated genetic relationships that could explain response to therapy. In this study, ML techniques were used to investigate the relationship between genetic variations affecting more than 60 candidate genes and carboplatin‐induced, taxane‐induced, and bevacizumab‐induced toxicities in 171 patients with ovarian cancer enrolled in the MITO‐16A/MaNGO‐OV2A trial. Single‐nucleotide variation (SNV, formerly SNP) profiles were examined using ML to find and prioritize those associated with drug‐induced toxicities, specifically hypertension, hematological toxicity, nonhematological toxicity, and proteinuria. The Boruta algorithm was used in cross‐validation to determine the significance of SNVs in predicting toxicities. Important SNVs were then used to train eXtreme gradient boosting models. During cross‐validation, the models achieved reliable performance with a Matthews correlation coefficient ranging from 0.375 to 0.410. A total of 43 SNVs critical for predicting toxicity were identified. For each toxicity, key SNVs were used to create a polygenic toxicity risk score that effectively divided individuals into high‐risk and low‐risk categories. In particular, compared with low‐risk individuals, high‐risk patients were 28‐fold more likely to develop hypertension. The proposed method provided insightful data to improve precision medicine for patients with ovarian cancer, which may be useful for reducing toxicities and improving toxicity management. [ABSTRACT FROM AUTHOR]