Role of gut microbiota in neuropathy and neuropathic pain states: A systematic preclinical review.

Gut microbiota has implications in Central Nervous System (CNS) disorders. Our study systematically identified preclinical studies aimed to investigate the possible gut microbiota contribution in neuropathy and neuropathic pain. The systematic review is reported in accordance with PRISMA checklist and guidelines outlined updated to 2020. We included research articles reporting neuropathy-related behavioral evaluations and/or neurological scores coupled to gut microbiota analysis performed by high-throughput technologies in the last ten years. Two investigators performed a search through 3 electronic bibliographic databases for full-text articles (PubMed, Scopus, and EMBASE) and three registries (Prospero, SyRF, and bioRxiv), cross-references, and linear searches. We assessed the methodological quality via the CAMARADES checklist and appraised the heterogeneous body of evidence by narrative synthesis. In total, there were 19 eligible studies. The most of these reports showed significant changes in gut microbiota setting in neuropathy conditions. The major gut microbiome remodeling was through fecal microbiome transplantation. Mechanistic proof of the gut-CNS communication was achieved by measuring inflammatory mediators, metabolic products, or neurotransmitters. As a limitation, we found considerable heterogeneity across eligible studies. We conclude that the current understanding of preclinical findings suggested an association between neuropathy and/or neuropathic pain and gut microbiota modifications. Our analysis provides the basis for further studies targeting microbiota for managing symptoms of neuropathy or other neuroinflammation-based CNS disorders. The systematic review protocol was registered on the international database Prospero under the registration number (257628).

Comparative Proteomic Profiling of Secreted Extracellular Vesicles from Breast Fibroadenoma and Malignant Lesions: A Pilot Study.

Extracellular vesicles (EVs) shuttle proteins, RNA, DNA, and lipids crucial for cell-to-cell communication. Recent findings have highlighted that EVs, by virtue of their cargo, may also contribute to breast cancer (BC) growth and metastatic dissemination. Indeed, EVs are gaining great interest as non-invasive cancer biomarkers. However, little is known about the biological and physical properties of EVs from malignant BC lesions, and even less is understood about EVs from non-malignant lesions, such as breast fibroadenoma (FAD), which are clinically managed using conservative approaches. Thus, for this pilot study, we attempted to purify and explore the proteomic profiles of EVs from benign breast lesions, HER2+ BCs, triple-negative BCs (TNBCs), and continuous BC cell lines (i.e., BT-549, MCF-10A, and MDA-MB-231), combining experimental and semi-quantitative approaches. Of note, proteome-wide analyses showed 49 common proteins across EVs harvested from FAD, HER2+ BCs, TNBCs, and model BC lines. This is the first feasibility study evaluating the physicochemical composition and proteome of EVs from benign breast cells and primary and immortalized BC cells. Our preliminary results hold promise for possible implications in precision medicine for BC.

The New Paradigm of Network Medicine to Analyze Breast Cancer Phenotypes.

Breast cancer (BC) is a heterogeneous and complex disease as witnessed by the existence of different subtypes and clinical characteristics that poses significant challenges in disease management. The complexity of this tumor may rely on the highly interconnected nature of the various biological processes as stated by the new paradigm of Network Medicine. We explored The Cancer Genome Atlas (TCGA)-BRCA data set, by applying the network-based algorithm named SWItch Miner, and mapping the findings on the human interactome to capture the molecular interconnections associated with the disease modules. To characterize BC phenotypes, we constructed protein-protein interaction modules based on "hub genes", called switch genes, both common and specific to the four tumor subtypes. Transcriptomic profiles of patients were stratified according to both clinical (immunohistochemistry) and genetic (PAM50) classifications. 266 and 372 switch genes were identified from immunohistochemistry and PAM50 classifications, respectively. Moreover, the identified switch genes were functionally characterized to select an interconnected pathway of disease genes. By intersecting the common switch genes of the two classifications, we selected a unique signature of 28 disease genes that were BC subtype-independent and classification subtype-independent. Data were validated both in vitro (10 BC cell lines) and ex vivo (66 BC tissues) experiments. Results showed that four of these hub proteins (AURKA, CDC45, ESPL1, and RAD54L) were over-expressed in all tumor subtypes. Moreover, the inhibition of one of the identified switch genes (AURKA) similarly affected all BC subtypes. In conclusion, using a network-based approach, we identified a common BC disease module which might reflect its pathological signature, suggesting a new vision to face with the disease heterogeneity.

Junctional adhesion molecule-A is down-regulated in anaplastic thyroid carcinomas and reduces cancer cell aggressiveness by modulating p53 and GSK3 α/ß pathways.

Junctional adhesion molecule A (JAM-A) is a transmembrane protein that contributes to different biological process, including the epithelial to mesenchymal transition (EMT). Through an EMT profiler array, we explored the molecular players associated with human thyroid cancer progression and identified JAM-A as one of the genes mostly deregulated. The quantitative real-time polymerase chain reaction and immunohistochemistry analyses showed that downregulation of JAM-A occurred in anaplastic thyroid carcinoma (ATC) compared with normal thyroid (NT) and papillary thyroid carcinoma (PTC) tissues and correlated with extrathyroid infiltration, tumor size, and ATC histotype. In ATC cell lines, JAM-A restoration suppressed malignant hallmarks of transformation including cell proliferation, motility, and transendothelial migration. Accordingly, knockdown of JAM-A enhanced thyroid cancer cell proliferation and motility in PTC cells. Through the proteome profiler human phospho-kinase array, we demonstrated that higher expression of JAM-A was associated with a significant increased level of phosphorylation of p53 and GSK3 α/ß proteins. In conclusion, our findings highlight a novel role of JAM-A in thyroid cancer progression and suggest that JAM-A restoration could have potential clinical relevance in thyroid cancer treatment.

Bringing radiomics into a multi-omics framework for a comprehensive genotype-phenotype characterization of oncological diseases.

Genomic and radiomic data integration, namely radiogenomics, can provide meaningful knowledge in cancer diagnosis, prognosis and treatment. Despite several data structures based on multi-layer architecture proposed to combine multi-omic biological information, none of these has been designed and assessed to include radiomic data as well. To meet this need, we propose to use the MultiAssayExperiment (MAE), an R package that provides data structures and methods for manipulating and integrating multi-assay experiments, as a suitable tool to manage radiogenomic experiment data. To this aim, we first examine the role of radiogenomics in cancer phenotype definition, then the current state of radiogenomics data integration in public repository and, finally, challenges and limitations of including radiomics in MAE, designing an extended framework and showing its application on a case study from the TCGA-TCIA archives. Radiomic and genomic data from 91 patients have been successfully integrated in a single MAE object, demonstrating the suitability of the MAE data structure as container of radiogenomic data.

Membrane disintegration by the antimicrobial peptide (P)GKY20: lipid segregation and domain formation.

Antimicrobial peptides (AMPs) are membrane-active peptides with a broad spectrum of activity against different pathogenic organisms and they represent promising new drugs to overcome the emergence of resistance to antibiotics in bacteria. (P)GKY20 is an antimicrobial peptide with a low hemolytic effect on eukaryotic cells and a strong antimicrobial activity especially against Gram-negative bacteria. However, its mechanism of action is still unknown. Here, we use fluorescence spectroscopy and differential scanning calorimetry combined with atomic force microscopy to characterise the binding of (P)GKY20 with model biomembranes and its effect on the membrane's microstructure and thermotropic properties. We found that (P)GKY20 selectively perturbs the bacterial-like membrane via a carpet-like mechanism employing peptide conformational changes, lipid segregation and domain formation as key steps in promoting membrane disruption. These results shed a first light on the action mechanism of (P)GKY20 and could represent an important contribution to the development of new peptides serving as antimicrobial agents.

TCGA-TCIA Impact on Radiogenomics Cancer Research: A Systematic Review.

In the last decade, the development of radiogenomics research has produced a significant amount of papers describing relations between imaging features and several molecular 'omic signatures arising from next-generation sequencing technology and their potential role in the integrated diagnostic field. The most vulnerable point of many of these studies lies in the poor number of involved patients. In this scenario, a leading role is played by The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA), which make available, respectively, molecular 'omic data and linked imaging data. In this review, we systematically collected and analyzed radiogenomic studies based on TCGA-TCIA data. We organized literature per tumor type and molecular 'omic data in order to discuss salient imaging genomic associations and limitations of each study. Finally, we outlined the potential clinical impact of radiogenomics to improve the accuracy of diagnosis and the prediction of patient outcomes in oncology.

Novel bioactive peptides from PD-L1/2, a type 1 ribosome inactivating protein from Phytolacca dioica L. Evaluation of their antimicrobial properties and anti-biofilm activities.

Antimicrobial peptides, also called Host Defence Peptides (HDPs), are effectors of innate immune response found in all living organisms. In a previous report, we have identified by chemical fragmentation, and characterized the first cryptic antimicrobial peptide in PD-L4, a type 1 ribosome inactivating protein (RIP) from leaves of Phytolacca dioica L. We applied a recently developed bioinformatic approach to a further member of the differently expressed pool of type 1 RIPs from P. dioica (PD-L1/2), and identified two novel putative cryptic HDPs in its N-terminal domain. These two peptides, here named IKY31 and IKY23, exhibit antibacterial activities against planktonic bacterial cells and, interestingly, significant anti-biofilm properties against two Gram-negative strains. Here, we describe that PD-L1/2 derived peptides are able to induce a strong dose-dependent reduction in biofilm biomass, affect biofilm thickness and, in the case of IKY31, interfere with cell-to-cell adhesion, likely by affecting biofilm structural components. In addition to these findings, we found that both PD-L1/2 derived peptides are able to assume stable helical conformations in the presence of membrane mimicking agents (SDS and TFE) and intriguingly beta structures when incubated with extracellular bacterial wall components (LPS and alginate). Overall, the data collected in this work provide further evidence of the importance of cryptic peptides derived from type 1 RIPs in host/pathogen interactions, especially under pathophysiological conditions induced by biofilm forming bacteria. This suggests a new possible role of RIPs as precursors of antimicrobial and anti-biofilm agents, likely released upon defensive proteolytic processes, which may be involved in plant homeostasis.

Chemical Cleavage of an Asp-Cys Sequence Allows Efficient Production of Recombinant Peptides with an N-Terminal Cysteine Residue.

Peptides with an N-terminal cysteine residue allow site-specific modification of proteins and peptides and chemical synthesis of proteins. They have been widely used to develop new strategies for imaging, drug discovery, diagnostics, and chip technologies. Here we present a method to produce recombinant peptides with an N-terminal cysteine residue as a convenient alternative to chemical synthesis. The method is based on the release of the desired peptide from a recombinant fusion protein by mild acid hydrolysis of an Asp-Cys sequence. To test the general validity of the method we prepared four fusion proteins bearing three different peptides (20-37 amino acid long) at the C-terminus of a ketosteroid isomerase-derived and two Onconase-derived carriers for the production of toxic peptides in E. coli. The chosen peptides were (C)GKY20, an antimicrobial peptide from the C-terminus of human thrombin, (C)ApoBL, an antimicrobial peptide from an inner region of human Apolipoprotein B, and (C)p53pAnt, an anticancer peptide containing the C-terminal region of the p53 protein fused to the cell penetrating peptide Penetratin. Cleavage efficiency of Asp-Cys bonds in the four fusion proteins was studied as a function of pH, temperature, and incubation time. In spite of the differences in the amino acid sequence (GTGDCGKY, GTGDCHVA, GSGTDCGSR, SQGSDCGSR) we obtained for all the proteins a cleavage efficiency of about 70-80% after 24 h incubation at 60 °C and pH 2. All the peptides were produced with very good yield (5-16 mg/L of LB cultures), high purity (>96%), and the expected content of free thiol groups (1 mol per mole of peptide). Furthermore, (C)GKY20 was modified with PyMPO-maleimide, a commercially available fluorophore bearing a thiol reactive group, and with 6-hydroxy-2-cyanobenzothiazole, a reagent specific for N-terminal cysteines, with yields of 100% thus demonstrating that our method is very well suited for the production of fully reactive peptides with an N-terminal cysteine residue.

Antimicrobial potency of cationic antimicrobial peptides can be predicted from their amino acid composition: Application to the detection of "cryptic" antimicrobial peptides.

Cationic antimicrobial peptides (CAMPs) are essential components of innate immunity. Here we show that antimicrobial potency of CAMPs is linearly correlated to the product CmHnL where C is the net charge of the peptide, H is a measure of its hydrophobicity and L its length. Exponents m and n define the relative contribution of charge and hydrophobicity to the antimicrobial potency. Very interestingly the values of m and n are strain specific. The ratio n/(m+n) can vary between ca. 0.5 and 1, thus indicating that some strains are sensitive to highly charged peptides, whereas others are particularly susceptible to more hydrophobic peptides. The slope of the regression line describing the correlation "antimicrobial potency"/"CmHnL product" changes from strain to strain indicating that some strains acquired a higher resistance to CAMPs than others. Our analysis provides also an effective computational strategy to identify CAMPs included inside the structure of larger proteins or precursors, which can be defined as "cryptic" CAMPs. We demonstrate that it is not only possible to identify and locate with very good precision the position of cryptic peptides, but also to analyze the internal structure of long CAMPs, thus allowing to draw an accurate map of the molecular determinants of their antimicrobial activity. A spreadsheet, provided in the Supplementary material, allows performing the analysis of protein sequences. Our strategy is also well suited to analyze large pools of sequences, thus significantly improving the identification of new CAMPs and the study of innate immunity.

miR-331-5p Affects Motility of Thyroid Cancer Cell Lines and Regulates BID Expression.

During tumorigenesis, miRNAs with unbalanced expression profiles can increase the threat of disease progression. Here, we focus on the role of miR-331-5p in the pathogenesis of thyroid cancer (TC). In vitro studies were conducted using TC cell lines after the forced expression and silencing of miR-331-5p. Cell proliferation and viability were analyzed via cell counts and colorimetric assays. Cell motility was analyzed via wound healing assays, Transwell migration and invasion assays, and Matrigel Matrix assays. The putative targets of miR-331-5p were unveiled via label-free proteomic screening and then verified using Western blot and luciferase assays. Expression studies were conducted by interrogating The Cancer Genome Atlas (TCGA). We found that ectopic miR-331-5p expression reduces TC cell motility, while miR-331-5p silencing induces the opposite phenotype. Proteomic screening revealed eight putative downregulated targets of miR-331-5p, among which BID was confirmed as a direct target. TCGA data showed the downregulation of miR-331-5p and the upregulation of BID in TC tissues. In summary, deregulation of the miR-331-5p/BID axis could enhance the aggressiveness of TC cell lines, providing new insights into the mechanisms of the progression of this disease and suggesting a potential role of the component factors as possible biomarkers in TC tissues.

The Oncosuppressive Properties of KCTD1: Its Role in Cell Growth and Mobility.

The KCTD protein family is traditionally regarded as proteins that play key roles in neurological physiopathology. However, new studies are increasingly demonstrating their involvement in many other biological processes, including cancers. This is particularly evident for KCTD proteins not involved in protein ubiquitination and degradation, such as KCTD1. We explored the role of KCTD1 in colorectal cancer by knocking down this protein in the human colon adenocarcinoma cell line, SW480. We re-assessed its ability to downregulate ß-catenin, a central actor in the WNT/ß-catenin signalling pathway. Interestingly, opposite effects are observed when the protein is upregulated in CACO2 colorectal cancer cells. Moreover, interrogation of the TCGA database indicates that KCTD1 downregulation is associated with ß-catenin overexpression in colorectal cancer patients. Indeed, knocking down KCTD1 in SW480 cells led to a significant increase in their motility and stemness, two important tumorigenesis traits, suggesting an oncosuppressor role for KCTD1. It is worth noting that similar effects are induced on colorectal cancer cells by the misregulation of KCTD12, a protein that is distantly related to KCTD1. The presented results further expand the spectrum of KCTD1 involvement in apparently unrelated physiopathological processes. The similar effects produced on colorectal cancer cell lines by KCTD1 and KCTD12 suggest novel, previously unreported analogous activities among members of the KCTD protein family.

Discovering Common miRNA Signatures Underlying Female-Specific Cancers via a Machine Learning Approach Driven by the Cancer Hallmark ERBB.

Big data processing, using omics data integration and machine learning (ML) methods, drive efforts to discover diagnostic and prognostic biomarkers for clinical decision making. Previously, we used the TCGA database for gene expression profiling of breast, ovary, and endometrial cancers, and identified a top-scoring network centered on the ERBB2 gene, which plays a crucial role in carcinogenesis in the three estrogen-dependent tumors. Here, we focused on microRNA expression signature similarity, asking whether they could target the ERBB family. We applied an ML approach on integrated TCGA miRNA profiling of breast, endometrium, and ovarian cancer to identify common miRNA signatures differentiating tumor and normal conditions. Using the ML-based algorithm and the miRTarBase database, we found 205 features and 158 miRNAs targeting ERBB isoforms, respectively. By merging the results of both databases and ranking each feature according to the weighted Support Vector Machine model, we prioritized 42 features, with accuracy (0.98), AUC (0.93-95% CI 0.917-0.94), sensitivity (0.85), and specificity (0.99), indicating their diagnostic capability to discriminate between the two conditions. In vitro validations by qRT-PCR experiments, using model and parental cell lines for each tumor type showed that five miRNAs (hsa-mir-323a-3p, hsa-mir-323b-3p, hsa-mir-331-3p, hsa-mir-381-3p, and hsa-mir-1301-3p) had expressed trend concordance between breast, ovarian, and endometrium cancer cell lines compared with normal lines, confirming our in silico predictions. This shows that an integrated computational approach combined with biological knowledge, could identify expression signatures as potential diagnostic biomarkers common to multiple tumors.

Novel Antimicrobial Strategies to Prevent Biofilm Infections in Catheters after Radical Cystectomy: A Pilot Study.

Catheter-associated infections in bladder cancer patients, following radical cystectomy or ureterocutaneostomy, are very frequent, and the development of antibiotic resistance poses great challenges for treating biofilm-based infections. Here, we characterized bacterial communities from catheters of patients who had undergone radical cystectomy for muscle-invasive bladder cancer. We evaluated the efficacy of conventional antibiotics, alone or combined with the human ApoB-derived antimicrobial peptide r(P)ApoBLAla, to treat ureteral catheter-colonizing bacterial communities on clinically isolated bacteria. Microbial communities adhering to indwelling catheters were collected during the patients' regular catheter change schedules (28 days) and extracted within 48 h. Living bacteria were characterized using selective media and biochemical assays. Biofilm growth and novel antimicrobial strategies were analyzed using confocal laser scanning microscopy. Statistical analyses confirmed the relevance of the biofilm reduction induced by conventional antibiotics (fosfomycin, ceftriaxone, ciprofloxacin, gentamicin, and tetracycline) and a well-characterized human antimicrobial peptide r(P)ApoBLAla (1:20 ratio, respectively). Catheters showed polymicrobial communities, with Enterobactericiae and Proteus isolates predominating. In all samples, we recorded a meaningful reduction in biofilms, in both biomass and thickness, upon treatment with the antimicrobial peptide r(P)ApoBLAla in combination with low concentrations of conventional antibiotics. The results suggest that combinations of conventional antibiotics and human antimicrobial peptides might synergistically counteract biofilm growth on ureteral catheters, suggesting novel avenues for preventing catheter-associated infections in patients who have undergone radical cystectomy and ureterocutaneostomy.

ABCA1, TCF7, NFATC1, PRKCZ, and PDGFA DNA methylation as potential epigenetic-sensitive targets in acute coronary syndrome via network analysis.

Acute coronary syndrome (ACS) is the most severe clinical manifestation of coronary heart disease.We performed an epigenome-wide analysis of circulating CD4+ and CD8+ T cells isolated from ACS patients and healthy subjects (HS), enrolled in the DIANA clinical trial, by reduced-representation bisulphite sequencing (RRBS). In CD4+ T cells, we identified 61 differentially methylated regions (DMRs) associated with 57 annotated genes (53% hyper- and 47% hypo-methylated) by comparing ACS patients vs HS. In CD8+ T cells, we identified 613 DMRs associated with 569 annotated genes (28% hyper- and 72% hypo-methylated) in ACS patients as compared to HS. In CD4+vs CD8+ T cells of ACS patients we identified 175 statistically significant DMRs associated with 157 annotated genes (41% hyper- and 59% hypo-methylated). From pathway analyses, we selected six differentially methylated hub genes (NFATC1, TCF7, PDGFA, PRKCB, PRKCZ, ABCA1) and assessed their expression levels by q-RT-PCR. We found an up-regulation of selected genes in ACS patients vs HS (P < 0.001). ABCA1, TCF7, PDGFA, and PRKCZ gene expression was positively associated with CK-MB serum concentrations (r = 0.75, P = 0.03; r = 0.760, P = 0.029; r = 0.72, P = 0.044; r = 0.74, P = 0.035, respectively).This pilot study is the first single-base resolution map of DNA methylome by RRBS in CD4+ and CD8+ T cells and provides specific methylation signatures to clarify the role of aberrant methylation in ACS pathogenesis, thus supporting future research for novel epigenetic-sensitive biomarkers in the prevention and early diagnosis of this pathology.

The impact of different preanalytical methods related to CA 15-3 determination in frozen human blood samples: a systematic review.

BACKGROUND: The determination of CA 15-3 is useful for monitoring breast cancer patients. Several retrospective studies determined CA 15-3 levels in frozen samples to evaluate the sensitivity and specificity of novel biomarkers in relation to breast cancer; however, freeze-thaw cycles, as well as preanalytical variables before sample storage, are not always reported. Here, we analyzed the current scientific literature to identify possible critical aspects related to CA 15-3 determination in frozen-stored human serum/plasma samples. METHODS: We obtained data from 4 different bibliographic databases: Web of Science, Embase, PubMed, and Cochrane Library. We followed the PRISMA guidelines to screen and select the eligible articles discussed in the final revision. RESULTS: Initially, 674 scientific papers were evaluated, and after the application of the screening and eligibility criteria, 18 studies were included in the qualitative synthesis. The analysis reported an important level of heterogeneity concerning the preanalytical phase before sample storage. CONCLUSION: Although advances in healthcare have been achieved using certified workflows in medical diagnostics, standardized preanalytical processes are not always applied when referring to frozen-stored biosamples. Biobanks will guarantee the best possible conditions for the storage of human biological samples to be used in clinical research. The use of certified bioresources will favor the optimal development and introduction of new disease biomarkers.

MuSA: a graphical user interface for multi-OMICs data integration in radiogenomic studies.

Analysis of large-scale omics data along with biomedical images has gaining a huge interest in predicting phenotypic conditions towards personalized medicine. Multiple layers of investigations such as genomics, transcriptomics and proteomics, have led to high dimensionality and heterogeneity of data. Multi-omics data integration can provide meaningful contribution to early diagnosis and an accurate estimate of prognosis and treatment in cancer. Some multi-layer data structures have been developed to integrate multi-omics biological information, but none of these has been developed and evaluated to include radiomic data. We proposed to use MultiAssayExperiment (MAE) as an integrated data structure to combine multi-omics data facilitating the exploration of heterogeneous data. We improved the usability of the MAE, developing a Multi-omics Statistical Approaches (MuSA) tool that uses a Shiny graphical user interface, able to simplify the management and the analysis of radiogenomic datasets. The capabilities of MuSA were shown using public breast cancer datasets from TCGA-TCIA databases. MuSA architecture is modular and can be divided in Pre-processing and Downstream analysis. The pre-processing section allows data filtering and normalization. The downstream analysis section contains modules for data science such as correlation, clustering (i.e., heatmap) and feature selection methods. The results are dynamically shown in MuSA. MuSA tool provides an easy-to-use way to create, manage and analyze radiogenomic data. The application is specifically designed to guide no-programmer researchers through different computational steps. Integration analysis is implemented in a modular structure, making MuSA an easily expansible open-source software.

Fighting multidrug resistance with a fruit extract: anti-cancer and anti-biofilm activities of Acca sellowiana.

In this study, the efficacy of Acca sellowiana fruit acetonic extract on human MDR cancer cells was tested for the first time, and it was demonstrated that the fruit extract is effective on both sensitive and resistant tumor cells. The effects of A. sellowiana extract on bacterial biofilm were also examined for the first time. By crystal violet assays and confocal microscopy analyses, it was demonstrated that the plant extract is able to strongly inhibit biofilm formation of both sensitive and resistant bacterial strains. Furthermore, antimicrobial activity assays and TEM analyses clearly demonstrated the effectiveness of plant extract on planktonic bacterial cells in both sensitive and resistant strains. Altogether, these findings intriguingly expand the panel of activities of A. sellowiana fruit extract with respect to previous reports, and open interesting perspectives to its therapeutic applications.

KCTD15 deregulation is associated with alterations of the NF-κB signaling in both pathological and physiological model systems.

Like other KCTD proteins, KCTD15 is involved in important albeit distinct biological processes as cancer, neural crest formation, and obesity. Here, we characterized the role of KCTD15 in different physiological/pathological states to gain insights into its diversified function(s). The silencing of KCTD15 in MLL-rearranged leukemia models induced attenuation of the NF-κB pathway associated with a downregulation of pIKK-ß and pIKB-α. Conversely, the activation of peripheral blood T cells upon PMA/ionomycin stimulation remarkably upregulated KCTD15 and, simultaneously, pIKK-ß and pIKB-α. Moreover, a significant upregulation of KCTD15 was also observed in CD34 hematopoietic stem/progenitor cells where the NF-κB pathway is physiologically activated. The association between KCTD15 upregulation and increased NF-κB signaling was confirmed by luciferase assay as well as KCTD15 and IKK-ß proximity ligation and immunoprecipitation experiments. The observed upregulation of IKK-ß by KCTD15 provides a novel and intriguing interpretative key for understanding the protein function in a wide class of physiological/pathological conditions ranging from neuronal development to cancer and obesity/diabetes.

The Impact of Normalization Approaches to Automatically Detect Radiogenomic Phenotypes Characterizing Breast Cancer Receptors Status.

In breast cancer studies, combining quantitative radiomic with genomic signatures can help identifying and characterizing radiogenomic phenotypes, in function of molecular receptor status. Biomedical imaging processing lacks standards in radiomic feature normalization methods and neglecting feature normalization can highly bias the overall analysis. This study evaluates the effect of several normalization techniques to predict four clinical phenotypes such as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and triple negative (TN) status, by quantitative features. The Cancer Imaging Archive (TCIA) radiomic features from 91 T1-weighted Dynamic Contrast Enhancement MRI of invasive breast cancers were investigated in association with breast invasive carcinoma miRNA expression profiling from the Cancer Genome Atlas (TCGA). Three advanced machine learning techniques (Support Vector Machine, Random Forest, and Naïve Bayesian) were investigated to distinguish between molecular prognostic indicators and achieved an area under the ROC curve (AUC) values of 86%, 93%, 91%, and 91% for the prediction of ER+ versus ER-, PR+ versus PR-, HER2+ versus HER2-, and triple-negative, respectively. In conclusion, radiomic features enable to discriminate major breast cancer molecular subtypes and may yield a potential imaging biomarker for advancing precision medicine.