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.

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.

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.

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 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.

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.

lncRNAs-mRNAs Co-Expression Network Underlying Childhood B-Cell Acute Lymphoblastic Leukaemia: A Pilot Study.

Long non-coding RNAs (lncRNAs) are emerging as key gene regulators in the pathogenesis and development of various cancers including B lymphoblastic leukaemia (B-ALL). In this pilot study, we used RNA-Seq transcriptomic data for identifying novel lncRNA-mRNA cooperative pairs involved in childhood B-ALL pathogenesis. We conceived a bioinformatic pipeline based on unsupervised PCA feature extraction approach and stringent statistical criteria to extract potential childhood B-ALL lncRNA signatures. We then constructed a co-expression network of the aberrantly expressed lncRNAs (30) and protein-coding genes (754). We cross-validated our in-silico findings on an independent dataset and assessed the expression levels of the most differentially expressed lncRNAs and their co-expressed mRNAs through ex vivo experiments. Using the guilt-by-association approach, we predicted lncRNA functions based on their perfectly co-expressed mRNAs (Spearman's correlation) that resulted closely disease-associated. We shed light on 24 key lncRNAs and their co-expressed mRNAs which may play an important role in B-ALL pathogenesis. Our results may be of clinical utility for diagnostic and/or prognostic purposes in paediatric B-ALL management.

New Roadmaps for Non-muscle-invasive Bladder Cancer With Unfavorable Prognosis.

About 70% of bladder cancers (BCs) are diagnosed as non-muscle-invasive BCs (NMIBCs), while the remaining are muscle-invasive BCs (MIBCs). The European Association of Urology (EAU) guidelines stratify NMIBCs into low, intermediate, and high risk for treatment options. Low-risk NMIBCs undergo only the transurethral resection of the bladder (TURB), whereas for intermediate-risk and high-risk NMIBCs, the transurethral resection of the bladder (TURB) with or without Bacillus Calmette-Guérin (BCG) immune or chemotherapy is the standard treatment. A minority of NMIBCs show unfavorable prognosis. High-risk NMIBCs have a high rate of disease recurrence and/or progression to muscle-invasive tumor and BCG treatment failure. The heterogeneous nature of NMIBCs poses challenges for clinical decision-making. In 2020, the EAU made some changes to NMIBCs BCG failure definitions and treatment options, highlighting the need for reliable molecular markers for improving the predictive accuracy of currently available risk tables. Nowadays, next-generation sequencing (NGS) has revolutionized the study of cancer biology, providing diagnostic, prognostic, and therapy response biomarkers in support of precision medicine. Integration of NGS with other cutting-edge technologies might help to decipher also bladder tumor surrounding aspects such as immune system, stromal component, microbiome, and urobiome; altogether, this might impact the clinical outcomes of NMBICs especially in the BCG responsiveness. This review focuses on NMIBCs with unfavorable prognoses, providing molecular prognostic factors from tumor immune and stromal cells, and the perspective of urobiome and microbiome profiling on therapy response. We provide information on the cornerstone of immunotherapy and new promising bladder-preserving treatments and ongoing clinical trials for BCG-unresponsive NMIBCs.

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.

Epigenetic-sensitive pathways in personalized therapy of major cardiovascular diseases.

The complex pathobiology underlying cardiovascular diseases (CVDs) has yet to be explained. Aberrant epigenetic changes may result from alterations in enzymatic activities, which are responsible for putting in and/or out the covalent groups, altering the epigenome and then modulating gene expression. The identification of novel individual epigenetic-sensitive trajectories at single cell level might provide additional opportunities to establish predictive, diagnostic and prognostic biomarkers as well as drug targets in CVDs. To date, most of studies investigated DNA methylation mechanism and miRNA regulation as epigenetics marks. During atherogenesis, big epigenetic changes in DNA methylation and different ncRNAs, such as miR-93, miR-340, miR-433, miR-765, CHROME, were identified into endothelial cells, smooth muscle cells, and macrophages. During man development, lipid metabolism, inflammation and homocysteine homeostasis, alter vascular transcriptional mechanism of fundamental genes such as ABCA1, SREBP2, NOS, HIF1. At histone level, increased HDAC9 was associated with matrix metalloproteinase 1 (MMP1) and MMP2 expression in pro-inflammatory macrophages of human carotid plaque other than to have a positive effect on toll like receptor signaling and innate immunity. HDAC9 deficiency promoted inflammation resolution and reverse cholesterol transport, which might block atherosclerosis progression and promote lesion regression. Here, we describe main human epigenetic mechanisms involved in atherosclerosis, coronary heart disease, ischemic stroke, peripheral artery disease; cardiomyopathy and heart failure. Different epigenetics mechanisms are activated, such as regulation by circular RNAs, as MICRA, and epitranscriptomics at RNA level. Moreover, in order to open new frontiers for precision medicine and personalized therapy, we offer a panoramic view on the most innovative bioinformatic tools designed to identify putative genes and molecular networks underlying CVDs in man.

An Integrative Computational Approach Based on Expression Similarity Signatures to Identify Protein-Protein Interaction Networks in Female-Specific Cancers.

Breast, ovarian, and endometrial cancers have a major impact on mortality in women. These tumors share hormone-dependent mechanisms involved in female-specific cancers which support tumor growth in a different manner. Integrated computational approaches may allow us to better detect genomic similarities between these different female-specific cancers, helping us to deliver more sophisticated diagnosis and precise treatments. Recently, several initiatives of The Cancer Genome Atlas (TCGA) have encouraged integrated analyses of multiple cancers rather than individual tumors. These studies revealed common genetic alterations (driver genes) even in clinically distinct entities such as breast, ovarian, and endometrial cancers. In this study, we aimed to identify expression similarity signatures by extracting common genes among TCGA breast (BRCA), ovarian (OV), and uterine corpus endometrial carcinoma (UCEC) cohorts and infer co-regulatory protein-protein interaction networks that might have a relationship with the estrogen signaling pathway. Thus, we carried out an unsupervised principal component analysis (PCA)-based computational approach, using RNA sequencing data of 2,015 female cancer and 148 normal samples, in order to simultaneously capture the data heterogeneity of intertumors. Firstly, we identified tumor-associated genes from gene expression profiles. Secondly, we investigated the signaling pathways and co-regulatory protein-protein interaction networks underlying these three cancers by leveraging the Ingenuity Pathway Analysis software. In detail, we discovered 1,643 expression similarity signatures (638 downregulated and 1,005 upregulated genes, with respect to normal phenotype), denoted as tumor-associated genes. Through functional genomic analyses, we assessed that these genes were involved in the regulation of cell-cycle-dependent mechanisms, including metaphase kinetochore formation and estrogen-dependent S-phase entry. Furthermore, we generated putative co-regulatory protein-protein interaction networks, based on upstream regulators such as the ERBB2/HER2 gene. Moreover, we provided an ad-hoc bioinformatics workflow with a manageable list of intertumor expression similarity signatures for the three female-specific cancers. The expression similarity signatures identified in this study might uncover potential estrogen-dependent molecular mechanisms promoting carcinogenesis.

KCTD15 is overexpressed in human childhood B-cell acute lymphoid leukemia.

Leukemic cells originate from the malignant transformation of undifferentiated myeloid/lymphoid hematopoietic progenitors normally residing in bone marrow. As the precise molecular mechanisms underlying this heterogeneous disease are yet to be disclosed, the identification and the validation of novel actors in leukemia is of extreme importance. Here, we show that KCTD15, a member of the emerging class of KCTD ((K)potassium Channel Tetramerization Domain containing) proteins, is strongly upregulated in patients affected by B-cell type acute lymphoblastic leukemia (B-ALL) and in continuous cell lines (RS4;11, REH, TOM-1, SEM) derived from this form of childhood leukemia. Interestingly, KCTD15 downregulation induces apoptosis and cell death suggesting that it has a role in cellular homeostasis and proliferation. In addition, stimulation of normal lymphocytes with the pokeweed mitogen leads to increased KCTD15 levels in a fashion comparable to those observed in proliferating leukemic cells. In this way, the role of KCTD15 is likely not confined to the B-ALL pathological state and extends to activation and proliferation of normal lymphocytes. Collectively, data here presented indicate that KCTD15 is an important and hitherto unidentified player in childhood lymphoid leukemia, and its study could open a new scenario for the identification of altered and still unknown molecular pathways in leukemia.

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.