Relationship between default mode network and resting-state electroencephalographic alpha rhythms in cognitively unimpaired seniors and patients with dementia due to Alzheimer's disease.

Here we tested the hypothesis of a relationship between the cortical default mode network (DMN) structural integrity and the resting-state electroencephalographic (rsEEG) rhythms in patients with Alzheimer's disease with dementia (ADD). Clinical and instrumental datasets in 45 ADD patients and 40 normal elderly (Nold) persons originated from the PDWAVES Consortium (www.pdwaves.eu). Individual rsEEG delta, theta, alpha, and fixed beta and gamma bands were considered. Freeware platforms served to derive (1) the (gray matter) volume of the DMN, dorsal attention (DAN), and sensorimotor (SMN) cortical networks and (2) the rsEEG cortical eLORETA source activities. We found a significant positive association between the DMN gray matter volume, the rsEEG alpha source activity estimated in the posterior DMN nodes (parietal and posterior cingulate cortex), and the global cognitive status in the Nold and ADD participants. Compared with the Nold, the ADD group showed lower DMN gray matter, lower rsEEG alpha source activity in those nodes, and lower global cognitive status. This effect was not observed in the DAN and SMN. These results suggest that the DMN structural integrity and the rsEEG alpha source activities in the DMN posterior hubs may be related and predict the global cognitive status in ADD and Nold persons.

Triple-Negative Breast Cancer EVs Modulate Growth and Migration of Normal Epithelial Lung Cells.

Breast cancer is the most common cancer amongst women worldwide. Recently, owing to screening programs and new technologies, the survival rate has increased significantly. Breast cancer can potentially develop metastases, and, despite them, lung metastases generally occur within five years of breast cancer diagnosis. In this study, the objective was to analyze the effect of breast cancer-derived EVs on a lung epithelial cell line. BEAS-2B cells were treated with extracellular vesicles (EVs) derived from triple-negative breast cancer cells (TNBCs), e.g., MDA-MB-231 and HS578T, separated using differential ultracentrifugation. We observed an increased growth, migration, and invasiveness of normal epithelial lung cells over time in the presence of TNBC EVs compared to the control. Therefore, these data suggest that EVs released by tumor cells contain biological molecules capable of influencing the pro-tumorigenic activity of normal cells. Exploring the role of EVs in oncology research and their potential cargo may be novel biomarkers for early cancer detection and further diagnosis.

Familial Dilated Cardiomyopathy: A Novel MED9 Short Isoform Identification.

Familial dilated cardiomyopathy (DCM) is among the leading indications for heart transplantation. DCM alters the transcriptomic profile. The alteration or activation/silencing of physiologically operating transcripts may explain the onset and progression of this pathological state. The mediator complex (MED) plays a fundamental role in the transcription process. The aim of this study is to investigate the MED subunits, which are altered in DCM, to identify target crossroads genes. RNA sequencing allowed us to identify specific MED subunits that are altered during familial DCM, transforming into human myocardial samples. N = 13 MED subunits were upregulated and n = 7 downregulated. MED9 alone was significantly reduced in patients compared to healthy subjects (HS) (FC = -1.257; p < 0.05). Interestingly, we found a short MED9 isoform (MED9s) (ENSG00000141026.6), which was upregulated when compared to the full-transcript isoform (MED9f). Motif identification analysis yielded several significant matches (p < 0.05), such as GATA4, which is downregulated in CHD. Moreover, although the protein-protein interaction network showed FOG2/ZFPM2, FOS and ID2 proteins to be the key interacting partners of GATA4, only FOG2/ZFPM2 overexpression showed an interaction score of "high confidence" ≥ 0.84. A significant change in the MED was observed during HF. For the first time, the MED9 subunit was significantly reduced between familial DCM and HS (p < 0.05), showing an increased MED9s isoform in DCM patients with respect to its full-length transcript. MED9 and GATA4 shared the same sequence motif and were involved in a network with FOG2/ZFPM2, FOS, and ID2, proteins already implicated in cardiac development.

Resting State Alpha Electroencephalographic Rhythms Are Affected by Sex in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment: A Retrospective and Exploratory Study.

In the present retrospective and exploratory study, we tested the hypothesis that sex may affect cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms recorded in normal elderly (Nold) seniors and patients with Alzheimer's disease and mild cognitive impairment (ADMCI). Datasets in 69 ADMCI and 57 Nold individuals were taken from an international archive. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands and fixed beta (14-30 Hz) and gamma (30-40 Hz) bands. Each group was stratified into matched females and males. The sex factor affected the magnitude of rsEEG source activities in the Nold seniors. Compared with the males, the females were characterized by greater alpha source activities in all cortical regions. Similarly, the parietal, temporal, and occipital alpha source activities were greater in the ADMCI-females than the males. Notably, the present sex effects did not depend on core genetic (APOE4), neuropathological (Aß42/phospho-tau ratio in the cerebrospinal fluid), structural neurodegenerative and cerebrovascular (MRI) variables characterizing sporadic AD-related processes in ADMCI seniors. These results suggest the sex factor may significantly affect neurophysiological brain neural oscillatory synchronization mechanisms underpinning the generation of dominant rsEEG alpha rhythms to regulate cortical arousal during quiet vigilance.

DNA Methylation Profile of the SREBF2 Gene in Human Fetal Aortas.

Increasing evidence suggests that maternal cholesterol represents an important risk factor for atherosclerotic disease in offspring already during pregnancy, although the underlying mechanisms have not yet been elucidated. Eighteen human fetal aorta samples were collected from the spontaneously aborted fetuses of normal cholesterolemic and hypercholesterolemic mothers. Maternal total cholesterol levels were assessed during hospitalization. DNA methylation profiling of the whole SREBF2 gene CpG island was performed (p value <0.05). The Mann-Whitney U test was used for comparison between the 2 groups. For the first time, our study revealed that in fetal aortas obtained from hypercholesterolemic mothers, the SREBF2 gene shows 4 significant differentially hypermethylated sites in the 5'UTR-CpG island. This finding indicates that more effective long-term primary cardiovascular prevention programs need to be designed for the offspring of mothers with hypercholesterolemia. Further studies should be conducted to clarify the epigenetic mechanisms underlying the association between early atherogenesis and maternal hypercholesterolemia during pregnancy.

The human aortic endothelium undergoes dose-dependent DNA methylation in response to transient hyperglycemia.

BACKGROUND: Glycemic control is a strong predictor of long-term cardiovascular risk in patients with diabetes mellitus, and poor glycemic control influences long-term risk of cardiovascular disease even decades after optimal medical management. This phenomenon, termed glycemic memory, has been proposed to occur due to stable programs of cardiac and endothelial cell gene expression. This transcriptional remodeling has been shown to occur in the vascular endothelium through a yet undefined mechanism of cellular reprogramming. METHODS: In the current study, we quantified genome-wide DNA methylation of cultured human endothelial aortic cells (HAECs) via reduced-representation bisulfite sequencing (RRBS) following exposure to diabetic (250 mg/dL), pre-diabetic (125 mg/dL), or euglycemic (100 mg/dL) glucose concentrations for 72 h (n = 2). RESULTS: We discovered glucose-dependent methylation of genomic regions (DMRs) encompassing 2199 genes, with a disproportionate number found among genes associated with angiogenesis and nitric oxide (NO) signaling-related pathways. Multi-omics analysis revealed differential methylation and gene expression of VEGF (↑5.6% DMR, ↑3.6-fold expression), and NOS3 (↓20.3% DMR, ↓1.6-fold expression), nodal regulators of angiogenesis and NO signaling, respectively. CONCLUSION: In the current exploratory study, we examine glucose-dependent and dose-responsive alterations in endothelial DNA methylation to examine a putative epigenetic mechanism underlying diabetic vasculopathy. Specifically, we uncover the disproportionate glucose-dependent methylation and gene expression of VEGF and NO signaling cascades, a physiologic imbalance known to cause endothelial dysfunction in diabetes. We therefore hypothesize that epigenetic mechanisms encode a glycemic memory within endothelial cells.

Abnormalities of Cortical Sources of Resting State Alpha Electroencephalographic Rhythms are Related to Education Attainment in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment.

In normal old (Nold) and Alzheimer's disease (AD) persons, a high cognitive reserve (CR) makes them more resistant and resilient to brain neuropathology and neurodegeneration. Here, we tested whether these effects may affect neurophysiological oscillatory mechanisms generating dominant resting state electroencephalographic (rsEEG) alpha rhythms in Nold and patients with mild cognitive impairment (MCI) due to AD (ADMCI). Data in 60 Nold and 70 ADMCI participants, stratified in higher (Edu+) and lower (Edu-) educational attainment subgroups, were available in an Italian-Turkish archive. The subgroups were matched for age, gender, and education. RsEEG cortical sources were estimated by eLORETA freeware. As compared to the Nold-Edu- subgroup, the Nold-Edu+ subgroup showed greater alpha source activations topographically widespread. On the contrary, in relation to the ADMCI-Edu- subgroup, the ADMCI-Edu+ subgroup displayed lower alpha source activations topographically widespread. Furthermore, the 2 ADMCI subgroups had matched cerebrospinal AD diagnostic biomarkers, brain gray-white matter measures, and neuropsychological scores. The current findings suggest that a high CR may be related to changes in rsEEG alpha rhythms in Nold and ADMCI persons. These changes may underlie neuroprotective effects in Nold seniors and subtend functional compensatory mechanisms unrelated to brain structure alterations in ADMCI patients.

Clinical connectome fingerprints of cognitive decline.

Brain connectome fingerprinting is rapidly rising as a novel influential field in brain network analysis. Yet, it is still unclear whether connectivity fingerprints could be effectively used for mapping and predicting disease progression from human brain data. We hypothesize that dysregulation of brain activity in disease would reflect in worse subject identification. We propose a novel framework, Clinical Connectome Fingerprinting, to detect individual connectome features from clinical populations. We show that "clinical fingerprints" can map individual variations between elderly healthy subjects and patients with mild cognitive impairment in functional connectomes extracted from magnetoencephalography data. We find that identifiability is reduced in patients as compared to controls, and show that these connectivity features are predictive of the individual Mini-Mental State Examination (MMSE) score in patients. We hope that the proposed methodology can help in bridging the gap between connectivity features and biomarkers of brain dysfunction in large-scale brain networks.

Improving staging of rectal cancer in the pelvis: the role of PET/MRI.

PURPOSE: The role of positron emission tomography/magnetic resonance (PET/MR) in evaluating the local extent of rectal cancer remains uncertain. This study aimed to investigate the possible role of PET/MR versus magnetic resonance (MR) in clinically staging rectal cancer. METHODS: This retrospective two-center cohort study of 62 patients with untreated rectal cancer investigated the possible role of baseline staging PET/MR versus stand-alone MR in determination of clinical stage. Two readers reviewed T and N stage, mesorectal fascia involvement, tumor length, distance from the anal verge, sphincter involvement, and extramural vascular invasion (EMVI). Sigmoidoscopy, digital rectal examination, and follow-up imaging, along with surgery when available, served as the reference standard. RESULTS: PET/MR outperformed MR in evaluating tumor size (42.5 ± 21.03 mm per the reference standard, 54 ± 20.45 mm by stand-alone MR, and 44 ± 20 mm by PET/MR, P = 0.004), and in identifying N status (correct by MR in 36/62 patients [58%] and by PET/MR in 49/62 cases [79%]; P = 0.02) and external sphincter infiltration (correct by MR in 6/10 and by PET/MR in 9/10; P = 0.003). No statistically significant differences were observed in relation to any other features. CONCLUSION: PET/MR provides a more precise assessment of the local extent of rectal cancers in evaluating cancer length, N status, and external sphincter involvement. PET/MR offers the opportunity to improve clinical decision-making, especially when evaluating low rectal tumors with possible external sphincter involvement.

An international expert opinion statement on the utility of PET/MR for imaging of skeletal metastases.

BACKGROUND: MR is an important imaging modality for evaluating musculoskeletal malignancies owing to its high soft tissue contrast and its ability to acquire multiparametric information. PET provides quantitative molecular and physiologic information and is a critical tool in the diagnosis and staging of several malignancies. PET/MR, which can take advantage of its constituent modalities, is uniquely suited for evaluating skeletal metastases. We reviewed the current evidence of PET/MR in assessing for skeletal metastases and provided recommendations for its use. METHODS: We searched for the peer reviewed literature related to the usage of PET/MR in the settings of osseous metastases. In addition, expert opinions, practices, and protocols of major research institutions performing research on PET/MR of skeletal metastases were considered. RESULTS: Peer-reviewed published literature was included. Nuclear medicine and radiology experts, including those from 13 major PET/MR centers, shared the gained expertise on PET/MR use for evaluating skeletal metastases and contributed to a consensus expert opinion statement. [18F]-FDG and non [18F]-FDG PET/MR may provide key advantages over PET/CT in the evaluation for osseous metastases in several primary malignancies. CONCLUSION: PET/MR should be considered for staging of malignancies where there is a high likelihood of osseous metastatic disease based on the characteristics of the primary malignancy, hight clinical suspicious and in case, where the presence of osseous metastases will have an impact on patient management. Appropriate choice of tumor-specific radiopharmaceuticals, as well as stringent adherence to PET and MR protocols, should be employed.

Radiomic and Genomic Machine Learning Method Performance for Prostate Cancer Diagnosis: Systematic Literature Review.

BACKGROUND: Machine learning algorithms have been drawing attention at the joining of pathology and radiology in prostate cancer research. However, due to their algorithmic learning complexity and the variability of their architecture, there is an ongoing need to analyze their performance. OBJECTIVE: This study assesses the source of heterogeneity and the performance of machine learning applied to radiomic, genomic, and clinical biomarkers for the diagnosis of prostate cancer. One research focus of this study was on clearly identifying problems and issues related to the implementation of machine learning in clinical studies. METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol, 816 titles were identified from the PubMed, Scopus, and OvidSP databases. Studies that used machine learning to detect prostate cancer and provided performance measures were included in our analysis. The quality of the eligible studies was assessed using the QUADAS-2 (quality assessment of diagnostic accuracy studies-version 2) tool. The hierarchical multivariate model was applied to the pooled data in a meta-analysis. To investigate the heterogeneity among studies, I2 statistics were performed along with visual evaluation of coupled forest plots. Due to the internal heterogeneity among machine learning algorithms, subgroup analysis was carried out to investigate the diagnostic capability of machine learning systems in clinical practice. RESULTS: In the final analysis, 37 studies were included, of which 29 entered the meta-analysis pooling. The analysis of machine learning methods to detect prostate cancer reveals the limited usage of the methods and the lack of standards that hinder the implementation of machine learning in clinical applications. CONCLUSIONS: The performance of machine learning for diagnosis of prostate cancer was considered satisfactory for several studies investigating the multiparametric magnetic resonance imaging and urine biomarkers; however, given the limitations indicated in our study, further studies are warranted to extend the potential use of machine learning to clinical settings. Recommendations on the use of machine learning techniques were also provided to help researchers to design robust studies to facilitate evidence generation from the use of radiomic and genomic biomarkers.

Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel.

The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12 Hz) and widespread delta (< 4 Hz) and theta (4-8 Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes.

Amygdalar nuclei and hippocampal subfields on MRI: Test-retest reliability of automated volumetry across different MRI sites and vendors.

BACKGROUND: The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults. METHODS: Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session. RESULTS: Significant MRI site and vendor effects (p â€‹< â€‹.05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman's r correlations >0.43, p â€‹< â€‹1.39E-36). In particular, volumes larger than 200 â€‹mm3 (for amygdalar nuclei) and 300 â€‹mm3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε â€‹< â€‹5% and DICE â€‹> â€‹0.80). CONCLUSION: Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials.

miR-622 is a novel potential biomarker of breast carcinoma and impairs motility of breast cancer cells through targeting NUAK1 kinase.

BACKGROUND: Aberrant expression of microRNAs (miR) has been proposed as non-invasive biomarkers for breast cancers. The aim of this study was to analyse the miR-622 level in the plasma and in tissues of breast cancer patients and to explore the role of miR-622 and its target, the NUAK1 kinase, in this context. METHODS: miR-622 expression was analysed in plasma and in tissues samples of breast cancer patients by q-RT-PCR. Bioinformatics programs, luciferase assay, public dataset analysis and functional experiments were used to uncover the role of miR-622 and its target in breast cancer cells. RESULTS: miR-622 is downregulated in plasma and in tissues of breast cancer patients respect to healthy controls and its downregulation is significantly associated with advanced grade and high Ki67 level. Modulation of miR-622 affects the motility phenotype of breast cancer cells. NUAK1 kinase is a functional target of miR-622, it is associated with poor clinical outcomes of breast cancer patients and is inversely correlated with miR-622 level. CONCLUSIONS: miR-622/NUAK1 axis is deregulated in breast cancer patients and affects the motility phenotype of breast cancer cells. Importantly, miR-622 and NUAK1 hold promises as biomarkers and as targets for breast cancers.

Chronic BACE-1 Inhibitor Administration in TASTPM Mice (APP KM670/671NL and PSEN1 M146V Mutation): An EEG Study.

OBJECTIVE: In this exploratory study, we tested whether electroencephalographic (EEG) rhythms may reflect the effects of a chronic administration (4 weeks) of an anti-amyloid ß-site amyloid precursor protein (APP) cleaving enzyme 1 inhibitor (BACE-1; ER-901356; Eisai Co., Ltd., Tokyo, Japan) in TASTPM (double mutation in APP KM670/671NL and PSEN1 M146V) producing Alzheimer's disease (AD) amyloid neuropathology as compared to wild type (WT) mice. METHODS: Ongoing EEG rhythms were recorded from a bipolar frontoparietal and two monopolar frontomedial (prelimbic) and hippocampal channels in 11 WT Vehicle, 10 WT BACE-1, 10 TASTPM Vehicle, and 11 TASTPM BACE-1 mice (males; aged 8/9 months old at the beginning of treatment). Normalized EEG power (density) was compared between the first day (Day 0) and after 4 weeks (Week 4) of the BACE-1 inhibitor (10 mg/Kg) or vehicle administration in the 4 mouse groups. Frequency and magnitude of individual EEG delta and theta frequency peaks (IDF and ITF) were considered during animal conditions of behaviorally passive and active wakefulness. Cognitive status was not tested. RESULTS: Compared with the WT group, the TASTPM group generally showed a significantly lower reactivity in frontoparietal ITF power during the active over the passive condition (p < 0.05). Notably, there was no other statistically significant effect (e.g., additional electrodes, recording time, and BACE-1 inhibitor). CONCLUSIONS: The above EEG biomarkers reflected differences between the WT and TASTPM groups, but no BACE-1 inhibitor effect. The results suggest an enhanced experimental design with the use of younger mice, longer drug administrations, an effective control drug, and neuropathological amyloid markers.

Biobanking in health care: evolution and future directions.

BACKGROUND: The aim of the present review is to discuss how the promising field of biobanking can support health care research strategies. As the concept has evolved over time, biobanks have grown from simple biological sample repositories to complex and dynamic units belonging to large infrastructure networks, such as the Pan-European Biobanking and Biomolecular Resources Research Infrastructure (BBMRI). Biobanks were established to support scientific knowledge. Different professional figures with varied expertise collaborate to obtain and collect biological and clinical data from human subjects. At same time biobanks preserve the human and legal rights of each person that offers biomaterial for research. METHODS: A literature review was conducted in April 2019 from the online database PubMed, accessed through the Bibliosan platform. Four primary topics related to biobanking will be discussed: (i) evolution, (ii) bioethical issues, (iii) organization, and (iv) imaging. RESULTS: Most biobanks were founded as local units to support specific research projects, so they evolved in a decentralized manner. The consequence is an urgent needing for procedure harmonization regarding sample collection, processing, and storage. Considering the involvement of biomaterials obtained from human beings, different ethical issues such as the informed consent model, sample ownership, veto rights, and biobank sustainability are debated. In the face of these methodological and ethical challenges, international organizations such as BBMRI play a key role in supporting biobanking activities. Finally, a unique development is the creation of imaging biobanks that support the translation of imaging biomarkers (identified using a radiomic approach) into clinical practice by ensuring standardization of data acquisition and analysis, accredited technical validation, and transparent sharing of biological and clinical data. CONCLUSION: Modern biobanks permit large-scale analysis for individuation of specific diseases biomarkers starting from biological or digital material (i.e., bioimages) with well-annotated clinical and biological data. These features are essential for improving personalized medical approaches, where effective biomarker identification is a critical step for disease diagnosis and prognosis.

Relationship between functional imaging and immunohistochemical markers and prediction of breast cancer subtype: a PET/MRI study.

PURPOSE: The aim of this study was to determine if functional parameters extracted from the hybrid positron emission tomography/magnetic resonance imaging (PET/MRI) correlate with the immunohistochemical markers of breast cancer (BC) lesions, to assess their ability to predict BC subtype. METHODS: This prospective study was approved by the institution's Ethics Committee, and all patients provided written informed consent. A total of 50 BC patients at diagnosis underwent PET/MRI before pharmacological and surgical treatment. For each primary lesion, the following data were extracted: morphological data including tumour-node-metastasis stage and lesion size; apparent diffusion coefficient (ADC); perfusion data including forward volume transfer constant (Ktrans), reverse efflux volume transfer constant (Kep) and extravascular extracellular space volume (Ve); and metabolic data including standardized uptake value (SUV), lean body mass (SUL), metabolic tumour volume and total lesion glycolysis. Immunohistochemical reports were used to determine receptor status (oestrogen, progesterone, and human epidermal growth factor receptor 2), cellular differentiation status (grade), and proliferation index (Ki67) of the tumour lesions. Correlation studies (Mann-Whitney U test and Spearman's test), receiver operating characteristic (ROC) curve analysis, and multivariate analysis were performed. RESULTS: Association studies were performed to assess the correlations between imaging and histological prognostic markers of BC. Imaging biomarkers, which significantly correlated with biological markers, were selected to perform ROC curve analysis to determine their ability to discriminate among BC subtypes. SUVmax, SUVmean and SUL were able to discriminate between luminal A and luminal B subtypes (AUCSUVmean = 0.799; AUCSUVmax = 0.833; AUCSUL = 0.813) and between luminal A and nonluminal subtypes (AUCSUVmean = 0.926; AUCSUVmax = 0.917; AUCSUL = 0.945), and the lowest SUV and SUL values were associated with the luminal A subtype. Kepmax was able to discriminate between luminal A and luminal B subtypes (AUC = 0.779), and its highest values were associated with the luminal B subtype. Ktransmax (AUC = 0.881) was able to discriminate between luminal A and nonluminal subtypes, and the highest perfusion values were associated with the nonluminal subtype. In addition, ADC (AUC = 0.877) was able to discriminate between luminal B and nonluminal subtypes, and the lowest ADCmean values were associated with the luminal B subtype. Multivariate analysis was performed to develop a prognostic model, and the best predictive model included Ktransmax and SUVmax parameters. CONCLUSION: Using multivariate analysis of both PET and MRI parameters, a prognostic model including Ktransmax and SUVmax was able to predict the tumour subtype in 38 of 49 patients (77.6%, p < 0.001), with higher accuracy for the luminal B subtype (86.2%).

PET/MR in invasive ductal breast cancer: correlation between imaging markers and histological phenotype.

BACKGROUND: Differences in genetics and receptor expression (phenotypes) of invasive ductal breast cancer (IDC) impact on prognosis and treatment response. Immunohistochemistry (IHC), the most used technique for IDC phenotyping, has some limitations including its invasiveness. We explored the possibility of contrast-enhanced positron emission tomography magnetic resonance (CE-FDG PET/MR) to discriminate IDC phenotypes. METHODS: 21 IDC patients with IHC assessment of oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor-2 (HER2), and antigen Ki-67 (Ki67) underwent CE-FDG PET/MR. Magnetic resonance-perfusion biomarkers, apparent diffusion coefficient (ADC), and standard uptake value (SUV) were compared with IHC markers and phenotypes, using a Student's t-test and one-way ANOVA. RESULTS: ER/PR- tumours demonstrated higher Kepmean and SUVmax than ER or PR+ tumours. HER2- tumours displayed higher ADCmean, Kepmean, and SUVmax than HER2+tumours. Only ADCmean discriminated Ki67⩽14% tumours (lower ADCmean) from Ki67>14% tumours. PET/MR biomarkers correlated with IHC phenotype in 13 out of 21 patients (62%; P=0.001). CONCLUSIONS: Positron emission tomography magnetic resonance might non-invasively help discriminate IDC phenotypes, helping to optimise individual therapy options.

Free water elimination improves test-retest reproducibility of diffusion tensor imaging indices in the brain: A longitudinal multisite study of healthy elderly subjects.

Free water elimination (FWE) in brain diffusion MRI has been shown to improve tissue specificity in human white matter characterization both in health and in disease. Relative to the classical diffusion tensor imaging (DTI) model, FWE is also expected to increase sensitivity to microstructural changes in longitudinal studies. However, it is not clear if these two models differ in their test-retest reproducibility. This study compares a bi-tensor model for FWE with DTI by extending a previous longitudinal-reproducibility 3T multisite study (10 sites, 7 different scanner models) of 50 healthy elderly participants (55-80 years old) scanned in two sessions at least 1 week apart. We computed the reproducibility of commonly used DTI metrics (FA: fractional anisotropy, MD: mean diffusivity, RD: radial diffusivity, and AXD: axial diffusivity), derived either using a DTI model or a FWE model. The DTI metrics were evaluated over 48 white-matter regions of the JHU-ICBM-DTI-81 white-matter labels atlas, and reproducibility errors were assessed. We found that relative to the DTI model, FWE significantly reduced reproducibility errors in most areas tested. In particular, for the FA and MD metrics, there was an average reduction of approximately 1% in the reproducibility error. The reproducibility scores did not significantly differ across sites. This study shows that FWE improves sensitivity and is thus promising for clinical applications, with the potential to identify more subtle changes. The increased reproducibility allows for smaller sample size or shorter trials in studies evaluating biomarkers of disease progression or treatment effects. Hum Brain Mapp 38:12-26, 2017. © 2016 Wiley Periodicals, Inc.

Polycomb YY1 is a critical interface between epigenetic code and miRNA machinery after exposure to hypoxia in malignancy.

Yin Yang 1 (YY1) is a member of polycomb protein family involved in epigenetic modifications and transcriptional controls. We have shown that YY1 acts as positive regulator of tumor growth and angiogenesis by interfering with the VEGFA network. Yet, the link between polycomb chromatin complex and hypoxia regulation of VEGFA is still poorly understood. Here, we establish that hypoxia impairs YY1 binding to VEGFA mRNA 3'UTR (p<0.001) in bone malignancy. Moreover, RNA immunoprecipitation reveals the formation of triplex nuclear complexes among YY1, VEGFA DNA, mRNA, and unreached about 200 fold primiRNA 200b and 200c via Dicer protein. In this complex, YY1 is necessary to maintain the steady-state level of VEGFA expression while its silencing increases VEGFA mRNA half-life at 4 h and impairs the maturation of miRNA 200b/c. Hypoxia promotes histone modification through ubiquitination both of YY1 and Dicer proteins. Hypoxia-mediated down-regulation of YY1 and Dicer changes post-transcriptional VEGFA regulation by resulting in the accumulation of primiRNA200b/c in comparison to mature miRNAs (p<0.001). Given the regulatory functions of VEGFA on cellular activities to promote neoangiogenesis, we conclude that YY1 acts as novel critical interface between epigenetic code and miRNAs machinery under chronic hypoxia in malignancy.