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Radiomics is a quantitative method able to analyze a high-throughput extraction of minable imaging features. Herein, we aim to develop a CT angiography-based radiomics analysis and machine learning model for carotid plaques to discriminate vulnerable from no vulnerable plaques.Thirty consecutive patients with carotid atherosclerosis were enrolled in this pilot study. At surgery, a binary classification of plaques was adopted ("hard" vs "soft"). Feature extraction was performed using the R software package Moddicom. Pairwise feature interdependencies were evaluated using the Spearman rank correlation coefficient. A univariate analysis was performed to assess the association between each feature and the plaque classification and chose top-ranked features. The feature predictive value was investigated using binary logistic regression. A stepwise backward elimination procedure was performed to minimize the Akaike information criterion (AIC). The final significant features were used to build the models for binary classification of carotid plaques, including logistic regression (LR), support vector machine (SVM), and classification and regression tree analysis (CART). All models were cross-validated using fivefold cross validation. Class-specific accuracy, precision, recall and F-measure evaluation metrics were used to quantify classifier output quality.A total of 230 radiomics features were extracted from each plaque. Pairwise Spearman correlation between features reported a high level of correlations, with more than 80% correlating with at least one other feature at |ρ| 0.8. After a stepwise backward elimination procedure, the entropy and volume features were found to be the most significantly associated with the two plaque groups (p 0.001), with AUCs of 0.92 and 0.96, respectively. The best performance was registered by the SVM classifier with the RBF kernel, with accuracy, precision, recall and F-score equal to 86.7, 92.9, 81.3 and 86.7%, respectively. The CART classification tree model for the entropy and volume features model achieved 86.7% well-classified plaques and an AUC of 0.987.This pilot study highlighted the potential of CTA-based radiomics and machine learning to discriminate plaque composition. This new approach has the potential to provide a reliable method to improve risk stratification in patients with carotid atherosclerosis.

Objective We evaluated sodium-glucose co-transporter2 (SGLT2) expression and the effect of SGLT2 inhibitor (SGLT2i) therapies on carotid plaques of asymptomatic diabetic and non-diabetic patients. Methods Plaques were obtained from 296 non-diabetic patients and 227 patients with type 2 diabetes undergoing carotid endarterectomy. 97 patients with type 2 diabetes were treated with SGLT2 inhibitors for 16 ± 4 months before endarterectomy. After propensity score matching analysis, patients with type 2 diabetes were categorized without (n = 87) and with SGLT2i therapy (n = 87). To investigate SGLT2 expression levels' effects on major adverse endpoints (MACE = stroke, transient ischemic attack, myocardial infarction, and death), we evaluated MACE outcomes at a 2-year follow-up. Results Compared to plaques from patients without diabetes, plaques from patients with diabetes had higher SGLT2 expression, inflammation, and oxidative stress, along with lower SIRT6 expression and collagen content. Compared with plaques from patients with diabetes, SGLT2i-treated patients with type 2 diabetes presented increased SIRT6 expression and collagen content and lowered inflammation and ion and oxidative stress, thus indicating a more stable plaque phenotype. These results supported in vitro observations on human aorta endothelial cells (EC) (TeloHAEC-cells). Indeed, EC treated with high glucose (25 mM) in the presence of SGLT2i (100 nM canagliflozin) presented higher SIRT6 expression and decreased mRNA and protein SGLT2 levels, nuclear factor-kappa B (NF-B(NF-κB), and matrix metallopeptidase 9 (MMP-9) expression compared to cells treated only with high glucose. After two years following endarterectomy, a multivariable Cox regression analysis showed significantly higher 2-year overall survival from MACE in patients without diabetes (P, Highlights • The identification of novel molecular targets of atherosclerosis progression is of utmost importance in diabetic patients. • The occurrence of SGLT2 receptors on the endothelial cells of atherosclerotic plaques may be an attractive therapeutic option for atherosclerosis in patients with diabetes. • SGLT2/SIRT6 represents an attractive option, given its crucial involvement in atherosclerosis progression. • The endothelial SGLT2 inhibition increases the endothelial expression of SIRT6, yielding an improved atherosclerotic plaque phenotype and 2-year outcome. • The impairment of the endothelial SGLT2/SIRT6 pathway worsens outcomes in atherosclerotic patients with diabetes; this may be a potential preventive target.

Atherosclerotic plaque instability and rupture in patients with asymptomatic carotid artery stenosis (ACAS) is a leading cause of major adverse cardiac events (MACE). This could be mainly evidenced in patients with pre-diabetes. Indeed, the altered glucose homeostasis and insulin resistance could cause over-inflammation of atherosclerotic plaque, favoring its conversion to unstable phenotype with rupture and MACE. Notably, metformin therapy reducing the metabolic distress and the inflammatory burden could reduce MACE in ACAS patients with pre-diabetes. In this setting, the microRNAs (miRs) could be used as molecular biomarkers of atherosclerosis progression, plaque rupture, and worse prognosis in normoglycemics (NG) versus pre-diabetics metformin users (PDMU) versus pre-diabetics non-metformin users (PDNMU). However, our study aimed to investigate a wide miRNA panel in peripheral blood exosomes from patients with ACAS divided in NG versus PDMU versus PDNMU, and to associate the circulating miRNA expression profiles with MACE at 2 years of follow-up after endarterectomy. The study included 234 patients with ACAS divided into NG (n = 125), PDNMU (n = 73), and PDMU (n = 36). The miRs’ expression profiles of circulating exosomes were determined at baseline and at 2 years of follow-up by Affymetrix microarrays from the patients’ plasma samples from any study cohort. Then we collected and analyzed MACE at 2 years of follow-up in NG versus PDMU versus PDNMU. Prediabetics versus NG had over-inflammation (p &lt, 0.05) and over expressed miR-24 and miR-27 at baseline. At 2 years of follow-up, PDNMU versus NG, PDMU versus NG, and PDNMU versus PDMU over-expressed inflammatory markers and miR-24, miR-27, miR-100, miR-126, and miR-133 (p &lt, 0.05). Finally, at the end of follow-up, we observed a significant difference about MACE comparing PDNMU versus NG (n = 27 (36.9%) versus n = 8 (6.4%), p &lt, 0.05), PDNMU versus PDMU (n = 27 (36.9%) versus n = 6 (16.6%), 0.05), and PDMU versus NG (n = 6 (16.6%) versus n = 8 (6.4%), 0.05). Admission glucose values (HR (hazard ratio) 1.020, CI (confidence of interval) 95% (1.001–1.038), p = 0.029), atheromatous carotid plaque (HR 5.373, CI 95% (1.251–11.079), p = 0.024), and miR-24 (HR 3.842, CI 95% (1.768–19.222), p = 0.011) predicted MACE at 2 years of follow-up. Specific circulating miRs could be over-expressed in pre-diabetics and specifically in PDNMU versus PDMU after endarterectomy. MiR24, hyperglycemia, and atheromatous plaque could predict MACE at 2 years of follow-up.

Extracellular vesicles (EVs) have become a key tool in the biotechnological landscape due to their well-documented ability to mediate intercellular communication. This feature has been explored and is under constant investigation by researchers, who have demonstrated the important role of EVs in several research fields ranging from oncology to immunology and diagnostics to regenerative medicine. Unfortunately, there are still some limitations to overcome before clinical application, including the inability to confine the EVs to strategically defined sites of interest to avoid side effects. In this study, for the first time, EV application is supported by 3D bioprinting technology to develop a new strategy for applying the angiogenic cargo of human umbilical vein endothelial cell-derived EVs in regenerative medicine. EVs, derived from human endothelial cells and grown under different stressed conditions, were collected and used as bioadditives for the formulation of advanced bioinks. After in vivo subcutaneous implantation, we demonstrated that the bioprinted 3D structures, loaded with EVs, supported the formation of a new functional vasculature in situ, consisting of blood-perfused microvessels recapitulating the printed pattern. The results obtained in this study favour the development of new therapeutic approaches for critical clinical conditions, such as the need for prompt revascularization of ischaemic tissues, which represent the fundamental substrate for advanced regenerative medicine applications.

Background: In this study we investigated the function of the non-catalytic region of tyrosine kinase adaptor protein 2 (NCK2) and its correlation with ITGB1 and ITGB4 integrins in driving ovarian cancer (OvCa) aggressiveness. We also evaluated whether NCK2 may influence prognosis in OvCa patients. Methods: Nanofluidic technology was used to analyze expression of NCK2 in 332 OvCa patients. To evaluate mRNA expression of NCK2, integrins and VEGFA in OvCa cell lines, qRT-PCR was performed. Stable NCK2 overexpression was obtained in OVCAR3. qRT-PCR and Western blot were performed to evaluate expression changes of VEGFA, vimentin, ITGB1, ITGB4, MMP2 and MMP9 under normoxia and hypoxia conditions. Coimmunoprecipitation (Co-IP) was performed in the A2780 cell line to study the interaction between NCK2 and proteins of interest. To investigate whether NCK2 can influence anchorage-independent growth, a soft agar assay was completed. Transwell invasion assay was performed on stable-transfected OVCAR-3 cell lines. Results: Nanofluidic data showed NCK2 can play an important role as a factor promoting tumor aggressiveness and survival in OvCa. This role was also linked to the behaviors of ITGB1 and ITGB4. Moreover, in cells overexpressing NCK2, the expression of vimentin, MMP2, MMP9, VEGFA and ITGB1, but not of ITGB4 was induced by hypoxia. Co-IP showed that NCK2 can directly bind ITGB1, but not VEGFA. NCK2 may be involved in mediating cell-extracellular matrix interactions in OvCa cells by influencing tumor aggressiveness. Conclusions: This study provides evidence of a possible role of NCK2 as biomarker of OvCa progression.

GBP1 and PIM1 are known to interact with a molar ratio 1:1. GBP1:PIM1 binding initiates a signaling pathway that induces resistance to common chemotherapeutics such as paclitaxel. Since GBP1 is a large GTPase which undergoes conformational changes in a nucleotide-dependent manner, we investigated the effect of GTP/GDP binding on GBP1:PIM1 interaction by using computational and biological studies. It resulted that only GTP decreases the formation of the GBP1:PIM1 complex through an allosteric mechanism, putting the bases for the identification of new compounds potentially able to revert resistance to paclitaxel.

Class III β-tubulin plays a prominent role in the development of drug resistance to paclitaxel by allowing the incorporation of the GBP1 GTPase into microtubules. Once in the cytoskeleton, GBP1 binds to prosurvival kinases such as PIM1 and initiates a signaling pathway that induces resistance to paclitaxel. Therefore, the inhibition of the GBP1:PIM1 interaction could potentially revert resistance to paclitaxel. A panel of 44 4-azapodophyllotoxin derivatives was screened in the NCI-60 cell panel. The result is that 31 are active and the comparative analysis demonstrated specific activity in paclitaxel-resistant cells. Using surface plasmon resonance, we were able to prove that NSC756093 is a potent in vitro inhibitor of the GBP1:PIM1 interaction and that this property is maintained in vivo in ovarian cancer cells resistant to paclitaxel. Through bioinformatics, molecular modeling, and mutagenesis studies, we identified the putative NSC756093 binding site at the interface between the helical and the LG domain of GBP1. According to our results by binding to this site, the NSC756093 compound is able to stabilize a conformation of GBP1 not suitable for binding to PIM1.

The Class III β-tubulin isotype (βIII-tubulin) is a predictive biomarker in ovarian cancer and other solid tumor malignancies. We discovered that βIII-tubulin function is linked to two GTPases: guanylate-binding protein 1 (GBP1), which activates its function, and GNAI1, which inhibits it. This finding was demonstrated in a panel of ovarian cancer cells resistant to several chemotherapeutic agents. Using a protein microarray, we identified PIM1 as the downstream partner of GBP1, recruited into the cytoskeleton under hypoxic conditions. The clinical value of these observations was tested by performing an archive study of 98 ovarian cancer patients, which demonstrated that the βIII-tubulin -/PIM1- cohort responded to treatment, exhibiting long overall survival (OS), while βIII-tubulin +/PIM+ patients experienced poor outcomes and OS times similar to patients receiving palliation alone. βIII-tubulin expression is commonly believed responsible for paclitaxel resistance due to its enhancement of the dynamic instability of microtubules, which counteracts the activity of taxanes. In contrast, our research reveals that βIII-tubulin behaves as a gateway for prosurvival signals, such as PIM1, to move into the cytoskeleton. When cells are exposed to microenvironmental stressors, they activate this pathway by telling the cytoskeleton to incorporate PIM1 through GBP1 and βIII-tubulin, which ultimately leads to drug resistance. This discovery reveals that βIII-tubulin does not act alone but requires partners to play its role. The discovery of such protein:protein interactions underlying this prosurvival cascade makes feasible the development of therapeutic approaches using novel compounds that are capable of inhibiting the transmission of prosurvival signals into the cytoskeleton.

Bcl-2 plays a prominent role in regulating the function of mitochondria during respiration and in determining the threshold of apoptotic sensitivity. Despite its relevance, the mechanism through which these processes are achieved is still unknown. Using surface plasmon resonance technology to monitor Bcl-2 multimerisation we discovered that a simple dimeric model does not fit with experimental data. A molecular model of the experimentally observed Bcl-2 homomeric complex has been developed. Accordingly, using a panel of mutants we identified in the loop a critical region for the process of Bcl-2 multimerisation. Our results indicate that the Bcl-2 loop posttranscriptional changes can modulate its ability to make homo and hetero-complexes, ultimately leading to functional modulation, suggesting an intriguing relationship between the ability of Bcl-2 to form multimeric complexes and its multi-functional role as a membrane channel. This article is part of a Special Issue entitled: 11th European Symposium on Calcium.

Objective: Class III β-tublin (TUBB3) is a potent prognostic biomarker for ovarian cancer and other solid tumors. In this work we have discovered a novel role for TUBB3 as a gateway for cytoskeletal prosurvival signals. Methods: Through a genomic screening of a cell line made resistant to a drug whose activity is TUBB3 dependent, we have identified two GTPases (GBP1 and GNAI1) whose expression is strictly related to TUBB3 expression. Using the technique of Far Western Blotting, we have demonstrated that these GTPases physically interact with TUBB3. At variance of TUBB3, the two GTPAses can be overexpressed in vitro. Therefore, they served as prey in a high density protein microarray to identify protein kinases capable to interact with them. Results: Using transient overexpression the functional role of the two GTPases was ascertained, with GBP1 capable to activate the TUBB3 pathway and GNAI1 with an inhibitory function on its. The physical interaction between the two GTPases and cytoskeletal proteins were proven with Far Western Blot. At variance with TUBB3, the two GTPases can be expressed as recombinant proteins. Taken advantage of this fact, the two proteins served as prey on high density protein array containing over 9,000 human proteins. At least 18 protein kinases were capabe to interact with either GBP1 or GNAI1 or both. Among these kinases, we focused our attention on PIM1. PIM1:TUBB3 correlation was proven in ovarian cancer cell lines, both sensitive and resistant to chemotherapeutics, using coimmunoprecipiation experiments and again far western blotting. For the first time, we discovered that PIM1 is expressed in the microtubules and its expression is directly related to resistance to Paclitaxel and Cisplatin, but not to Epothilone-B. Importantly, PIM1 is overexpressed in cytoskeleton in microtubules when TUBB3 pathway is activated in hypoxic conditions. Finally, to analyze the translational value of our findings, we performed immunohistochemical analysis of TUBB3 and PIM1 expression in a clinical subset of 98 ovarian cancer patients. This approach revealed that double negative patients (TUBB3 and PIM1) have an overall survival (median 76 months) better than that noticeable in double positive (median 29 months). Conclusions: TUBB3 is commonly believed as a simple mechanism of Paclitaxel-resistance. Instead, this work demonstrates that TUBB3 is a gateway for prosurvival signals like PIM1 into the cytoskeleton. Ovarian cancer patients exhibiting expression of both TUBB3 and PIM1 have high probability of drug resistance and extreme short survival and should be carefully monitored for response to first line chemotherapy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4055. doi:10.1158/1538-7445.AM2011-4055