Radiomics and artificial intelligence analysis by T2-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging to predict Breast Cancer Histological Outcome.

OBJECTIVE: The objective of the study was to evaluate the accuracy of radiomics features obtained by MR images to predict Breast Cancer Histological Outcome. METHODS: A total of 217 patients with malignant lesions were analysed underwent MRI examinations. Considering histological findings as the ground truth, four different types of findings were used in both univariate and multivariate analyses: (1) G1 + G2 vs G3 classification; (2) presence of human epidermal growth factor receptor 2 (HER2 + vs HER2 -); (3) presence of the hormone receptor (HR + vs HR -); and (4) presence of luminal subtypes of breast cancer. RESULTS: The best accuracy for discriminating HER2 + versus HER2 - breast cancers was obtained considering nine predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 88% on validation set). The best accuracy for discriminating HR + versus HR - breast cancers was obtained considering nine predictors by T2-weighted subtraction images and a decision tree (accuracy of 90% on validation set). The best accuracy for discriminating G1 + G2 versus G3 breast cancers was obtained considering 16 predictors by early phase T1-weighted subtraction images in a linear regression model with an accuracy of 75%. The best accuracy for discriminating luminal versus non-luminal breast cancers was obtained considering 27 predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 94% on validation set). CONCLUSIONS: The combination of radiomics analysis and artificial intelligence techniques could be used to support physician decision-making in prediction of Breast Cancer Histological Outcome.

The Impact of O6-Methylguanine-DNA Methyltransferase (MGMT) Promoter Methylation on the Outcomes of Patients with Leiomyosarcoma Treated with Dacarbazine.

Dacarbazine is an important drug in the therapeutic landscape of leiomyosarcoma (LMS). Alkylating agents are subjected to resistance mechanisms based on anti-apoptotic pathways and repair mechanisms, including the DNA repair enzyme O6-methylguanine-DNA methyltransferase (MGMT). In this retrospective study, the methylation status of the MGMT promoter in histological tumor samples from patients with LMS, dacarbazine-based regimens-treated, was measured and correlated with clinical outcomes aimed at optimizing the use of dacarbazine in soft tissue sarcomas. The patients with unmethylated MGMT had better outcomes than those with methylated MGMT. Patients without MGMT methylation had better Progression Free Survival (PFS) when aged ≥62 years compared to those aged <62 years, while PFS of patients with methylated MGMT was less favorable independently of age (p = 0.0054). The patients without a methylated MGMT gene had higher Disease control rate (DCR). These results are not in agreement with the role of the methylated MGMT gene in other tumors, and with this study, we demonstrated the correlation between methylated MGMT and poor prognosis; despite that, sample smallness, heterogeneity of LMS and of treatment history could be selection bias. Predictive markers of response to chemotherapies in sarcomas remain an unmet need.

PARP10 Mediates Mono-ADP-Ribosylation of Aurora-A Regulating G2/M Transition of the Cell Cycle.

Intracellular mono-ADP-ribosyltransferases (mono-ARTs) catalyze the covalent attachment of a single ADP-ribose molecule to protein substrates, thus regulating their functions. PARP10 is a soluble mono-ART involved in the modulation of intracellular signaling, metabolism and apoptosis. PARP10 also participates in the regulation of the G1- and S-phase of the cell cycle. However, the role of this enzyme in G2/M progression is not defined. In this study, we found that genetic ablation, protein depletion and pharmacological inhibition of PARP10 cause a delay in the G2/M transition of the cell cycle. Moreover, we found that the mitotic kinase Aurora-A, a previously identified PARP10 substrate, is actively mono-ADP-ribosylated (MARylated) during G2/M transition in a PARP10-dependent manner. Notably, we showed that PARP10-mediated MARylation of Aurora-A enhances the activity of the kinase in vitro. Consistent with an impairment in the endogenous activity of Aurora-A, cells lacking PARP10 show a decreased localization of the kinase on the centrosomes and mitotic spindle during G2/M progression. Taken together, our data provide the first evidence of a direct role played by PARP10 in the progression of G2 and mitosis, an event that is strictly correlated to the endogenous MARylation of Aurora-A, thus proposing a novel mechanism for the modulation of Aurora-A kinase activity.

Preoperative localisation of nonpalpable breast lesions using magnetic markers in a tertiary cancer centre.

BACKGROUND: We retrospectively evaluated safety and performance of magnetic seed localisation of nonpalpable breast lesions. METHODS: We reviewed records of patients with nonpalpable breast lesions preoperative localised by placing magnetic Magseed® marker between February 2019 and December 2020. During surgery, Sentimag® magnetic probe was used to localise the marker and guide surgery. Safety, lesion identification and excision with tumour with free margins and re-excision rate were assessed. RESULTS: A total of 77 Magseed® devices were placed into the breasts of 73 patients, 44 under ultrasound and 33 under stereotactic guidance (4 bilateral). All devices were retrieved as were the target lesions. Magnetic marker placement was successful in all cases without any adverse event. Intraoperative identification and excision of the localised lesion were successful in 77 of 77 of cases (100%). In three cases (all of them calcifications with the seed placed under stereotactic guidance), the seed did not reach the exact target position of the biopsy clip; thus, larger excision was needed, with localisation failure attributed to incorrect clip insertion (n = 1) or to clip dislocation (n = 2). Migration of the marker was negligible in all patients. Complete excision after the initial procedure with at least 1-mm disease-free margins was obtained in 74 out of 77 (96.1%) lesions. The re-excision rate was 3 out of 77 (4%). CONCLUSIONS: Magnetic marker localisation for nonpalpable breast lesions was safe, reliable, and effective in terms of lesion identification, excision with tumour-free margins and re-excision rate.

Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography.

PURPOSE: To evaluate radiomics features in order to: differentiate malignant versus benign lesions; predict low versus moderate and high grading; identify positive or negative hormone receptors; and discriminate positive versus negative human epidermal growth factor receptor 2 related to breast cancer. METHODS: A total of 182 patients with known breast lesions and that underwent Contrast-Enhanced Mammography were enrolled in this retrospective study. The reference standard was pathology (118 malignant lesions and 64 benign lesions). A total of 837 textural metrics were extracted by manually segmenting the region of interest from both craniocaudally (CC) and mediolateral oblique (MLO) views. Non-parametric Wilcoxon-Mann-Whitney test, receiver operating characteristic, logistic regression and tree-based machine learning algorithms were used. The Adaptive Synthetic Sampling balancing approach was used and a feature selection process was implemented. RESULTS: In univariate analysis, the classification of malignant versus benign lesions achieved the best performance when considering the original_gldm_DependenceNonUniformity feature extracted on CC view (accuracy of 88.98%). An accuracy of 83.65% was reached in the classification of grading, whereas a slightly lower value of accuracy (81.65%) was found in the classification of the presence of the hormone receptor; the features extracted were the original_glrlm_RunEntropy and the original_gldm_DependenceNonUniformity, respectively. The results of multivariate analysis achieved the best performances when using two or more features as predictors for classifying malignant versus benign lesions from CC view images (max test accuracy of 95.83% with a non-regularized logistic regression). Considering the features extracted from MLO view images, the best test accuracy (91.67%) was obtained when predicting the grading using a classification-tree algorithm. Combinations of only two features, extracted from both CC and MLO views, always showed test accuracy values greater than or equal to 90.00%, with the only exception being the prediction of the human epidermal growth factor receptor 2, where the best performance (test accuracy of 89.29%) was obtained with the random forest algorithm. CONCLUSIONS: The results confirm that the identification of malignant breast lesions and the differentiation of histological outcomes and some molecular subtypes of tumors (mainly positive hormone receptor tumors) can be obtained with satisfactory accuracy through both univariate and multivariate analysis of textural features extracted from Contrast-Enhanced Mammography images.

Radiomic and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to Detect Breast Malignant Lesions.

Purpose:The purpose of this study was to discriminate between benign and malignant breast lesions through several classifiers using, as predictors, radiomic metrics extracted from CEM and DCE-MRI images. In order to optimize the analysis, balancing and feature selection procedures were performed. Methods: Fifty-four patients with 79 histo-pathologically proven breast lesions (48 malignant lesions and 31 benign lesions) underwent both CEM and DCE-MRI. The lesions were retrospectively analyzed with radiomic and artificial intelligence approaches. Forty-eight textural metrics were extracted, and univariate and multivariate analyses were performed: non-parametric statistical test, receiver operating characteristic (ROC) and machine learning classifiers. Results: Considering the single metrics extracted from CEM, the best predictors were KURTOSIS (area under ROC curve (AUC) = 0.71) and SKEWNESS (AUC = 0.71) calculated on late MLO view. Considering the features calculated from DCE-MRI, the best predictors were RANGE (AUC = 0.72), ENERGY (AUC = 0.72), ENTROPY (AUC = 0.70) and GLN (gray-level nonuniformity) of the gray-level run-length matrix (AUC = 0.72). Considering the analysis with classifiers and an unbalanced dataset, no significant results were obtained. After the balancing and feature selection procedures, higher values of accuracy, specificity and AUC were reached. The best performance was obtained considering 18 robust features among all metrics derived from CEM and DCE-MRI, using a linear discriminant analysis (accuracy of 0.84 and AUC = 0.88). Conclusions: Classifiers, adjusted with adaptive synthetic sampling and feature selection, allowed for increased diagnostic performance of CEM and DCE-MRI in the differentiation between benign and malignant lesions.

Multidisciplinary Management of Retroperitoneal Sarcoma: Diagnosis, Prognostic Factors and Treatment.

Retroperitoneal sarcomas (RPS) are rare cancers whose management can be challenging due to various presentation patterns, multiple organ involvement, and a high local and distant recurrence rate. Histopathology and prognostic factors analysis are essential to predict the behaviour of the disease and plan the best therapeutic strategy. To date, surgery is still the main therapeutic option that guarantees a chance of cure from the primary disease. While chemotherapy and radiotherapy seem to be good options for controlling metastatic and recurrent irresectable disease, their role in the treatment of primary RPS remains unclear. This literature review aims to provide a comprehensive overview of the multidisciplinary aspects of RPS management in high-volume centres, summarising the diagnostic path, the prognostic factors, and the most suitable therapeutic options.

Malignant Sinonasal Tumors: Update on Histological and Clinical Management.

Tumors of nasal cavity and paranasal sinuses (TuNSs) are rare and heterogeneous malignancies, presenting different histological features and clinical behavior. We reviewed the literature about etiology, biology, and clinical features of TuNSs to define pathologic features and possible treatment strategies. From a diagnostic point of view, it is mandatory to have high expertise and perform an immunohistochemical assessment to distinguish between different histotypes. Due to the extreme rarity of these neoplasms, there are no standard and evidence-based therapeutic strategies, lacking prospective and large clinical trials. In fact, most studies are retrospective analyses. Surgery represents the mainstay of treatment of TuNSs for small and localized tumors allowing complete tumor removal. Locally advanced lesions require more demolitive surgery that should be always followed by adjuvant radio- or chemo-radiotherapy. Recurrent/metastatic disease requires palliative chemo- and/or radiotherapy. Many studies emphasize the role of specific genes mutations in the development of TuNSs like mutations in the exons 4-9 of the TP53 gene, in the exon 9 of the PIK3CA gene and in the promoter of the TERT gene. In the near future, this genetic assessment will have new therapeutic implications. Future improvements in the understanding of the etiology, biology, and clinical features of TuNSs are warranted to improve their management.

Radiomics in hepatic metastasis by colorectal cancer.

BACKGROUND: Radiomics is an emerging field and has a keen interest, especially in the oncology field. The process of a radiomics study consists of lesion segmentation, feature extraction, consistency analysis of features, feature selection, and model building. Manual segmentation is one of the most critical parts of radiomics. It can be time-consuming and suffers from variability in tumor delineation, which leads to the reproducibility problem of calculating parameters and assessing spatial tumor heterogeneity, particularly in large or multiple tumors. Radiomic features provides data on tumor phenotype as well as cancer microenvironment. Radiomics derived parameters, when associated with other pertinent data and correlated with outcomes data, can produce accurate robust evidence based clinical decision support systems. The principal challenge is the optimal collection and integration of diverse multimodal data sources in a quantitative manner that delivers unambiguous clinical predictions that accurately and robustly enable outcome prediction as a function of the impending decisions. METHODS: The search covered the years from January 2010 to January 2021. The inclusion criterion was: clinical study evaluating radiomics of liver colorectal metastases. Exclusion criteria were studies with no sufficient reported data, case report, review or editorial letter. RESULTS: We recognized 38 studies that assessed radiomics in mCRC from January 2010 to January 2021. Twenty were on different tpics, 5 corresponded to most criteria; 3 are review, or letter to editors; so 10 articles were included. CONCLUSIONS: In colorectal liver metastases radiomics should be a valid tool for the characterization of lesions, in the stratification of patients based on the risk of relapse after surgical treatment and in the prediction of response to chemotherapy treatment.

Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography in the Breast Lesions Classification.

The aim of the study was to estimate the diagnostic accuracy of textural features extracted by dual-energy contrast-enhanced mammography (CEM) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. In total, 80 patients with known breast lesion were enrolled in this prospective study according to regulations issued by the local Institutional Review Board. All patients underwent dual-energy CEM examination in both craniocaudally (CC) and double acquisition of mediolateral oblique (MLO) projections (early and late). The reference standard was pathology from a surgical specimen for malignant lesions and pathology from a surgical specimen or fine needle aspiration cytology, core or Tru-Cut needle biopsy, and vacuum assisted breast biopsy for benign lesions. In total, 104 samples of 80 patients were analyzed. Furthermore, 48 textural parameters were extracted by manually segmenting regions of interest. Univariate and multivariate approaches were performed: non-parametric Wilcoxon-Mann-Whitney test; receiver operating characteristic (ROC), linear classifier (LDA), decision tree (DT), k-nearest neighbors (KNN), artificial neural network (NNET), and support vector machine (SVM) were utilized. A balancing approach and feature selection methods were used. The univariate analysis showed low accuracy and area under the curve (AUC) for all considered features. Instead, in the multivariate textural analysis, the best performance considering the CC view (accuracy (ACC) = 0.75; AUC = 0.82) was reached with a DT trained with leave-one-out cross-variation (LOOCV) and balanced data (with adaptive synthetic (ADASYN) function) and a subset of three robust textural features (MAD, VARIANCE, and LRLGE). The best performance (ACC = 0.77; AUC = 0.83) considering the early-MLO view was reached with a NNET trained with LOOCV and balanced data (with ADASYN function) and a subset of ten robust features (MEAN, MAD, RANGE, IQR, VARIANCE, CORRELATION, RLV, COARSNESS, BUSYNESS, and STRENGTH). The best performance (ACC = 0.73; AUC = 0.82) considering the late-MLO view was reached with a NNET trained with LOOCV and balanced data (with ADASYN function) and a subset of eleven robust features (MODE, MEDIAN, RANGE, RLN, LRLGE, RLV, LZLGE, GLV_GLSZM, ZSV, COARSNESS, and BUSYNESS). Multivariate analyses using pattern recognition approaches, considering 144 textural features extracted from all three mammographic projections (CC, early MLO, and late MLO), optimized by adaptive synthetic sampling and feature selection operations obtained the best results (ACC = 0.87; AUC = 0.90) and showed the best performance in the discrimination of benign and malignant lesions.

Safety and Activity of Metronomic Temozolomide in Second-Line Treatment of Advanced Neuroendocrine Neoplasms.

BACKGROUND: Platinum-based chemotherapy is the mainstay of front-line treatment of patients affected by pluri-metastatic intermediate/high grade NeuroEndocrine Neoplasms (NENs). However, there are no standard second-line treatments at disease progression. Previous clinical experiences have evidenced that temozolomide (TMZ), an oral analog of dacarbazine, is active against NENs at standard doses of 150 to 200 mg/mq per day on days 1 to 5 of a 28-day cycle, even if a significant treatment-related toxicity is reported. METHODS: Metastatic NENs patients were treated at the ENETS (European NeuroEndocrine Tumor Society) center of excellence of Naples (Italy), from 2014 to 2017 with a second-line alternative metronomic schedule of TMZ, 75 mg/m2 per os "one week on/one week off". Toxicity was graded with NCI-CTC criteria v4.0; objective responses with RECIST v1.1 and performance status (PS) according to ECOG. RESULTS: Twenty-six consecutive patients were treated. Median age was 65.5 years. The predominant primary organs were pancreas and lung. Grading was G2 in 11 patients, G3 in 15. More than half of patients had a PS 2 (15 vs. 11 with PS 1). The median time-on-temozolomide therapy was 12.2 months (95% CI: 11.4-19.6). No G3/G4 toxicities were registered. Complete response was obtained in 1 patient, partial response in 4, stable disease in 19 (disease control rate: 92.3%), and progressive disease in 2. The median overall survival from TMZ start was 28.3 months. PS improved in 73% of patients. CONCLUSIONS: Metronomic TMZ is a suitable treatment for G2 and G3 NENs particularly in PS 2 patients. Prospective and larger trials are needed to confirm these results.

Aurora-A recruitment and centrosomal maturation are regulated by a Golgi-activated pool of Src during G2.

The Golgi apparatus is composed of stacks of cisternae laterally connected by tubules to form a ribbon-like structure. At the onset of mitosis, the Golgi ribbon is broken down into discrete stacks, which then undergo further fragmentation. This ribbon cleavage is required for G2/M transition, which thus indicates that a 'Golgi mitotic checkpoint' couples Golgi inheritance with cell cycle transition. We previously showed that the Golgi-checkpoint regulates the centrosomal recruitment of the mitotic kinase Aurora-A; however, how the Golgi unlinking regulates this recruitment was unknown. Here we show that, in G2, Aurora-A recruitment is promoted by activated Src at the Golgi. Our data provide evidence that Src and Aurora-A interact upon Golgi ribbon fragmentation; Src phosphorylates Aurora-A at tyrosine 148 and this specific phosphorylation is required for Aurora-A localization at the centrosomes. This process, pivotal for centrosome maturation, is a fundamental prerequisite for proper spindle formation and chromosome segregation.

[Late complete response after long remission from treatment with FOLFIRI-aflibercept for metastatic colorectal cancer after progression to FOLFOX-bevacizumab]. / Tardiva risposta completa dopo lunga remissione da trattamento con schedula FOLFIRI-aflibercept per cancro colorettale metastatico dopo progressione a schedula folfox-bevacizumab.

We report a case of a 59 years old man affected by an adenocarcinoma of the rectum RAS wild type with synchronous liver metastases, diagnosed on October, 2011. The patient underwent a left hemicolectomy with left hepatic lobectomy. In view of the recurrence of the disease from 18.01.2012 to 13.7.2012 we practiced first line chemotherapy with FOLFOX plus bevacizumab for 12 total cycles, obtaining a complete response, so the patient underwent clinical follow-up controls that proved negative until January, 2013, when, following the appearance of pain in the pelvis to the left, a total body PET with 18FDG was performed that documented the presence of bone metastases (left hemipelvis), confirmed histologically. Therefore from 03.18.2013 to 29.03.2013 the patient underwent a left ischium radiotherapy (for a total of 30 Gy). On May, 2013, a CT scan showed a progression of disease in the liver and so the patient started a II line chemotherapy with FOLFIRI and aflibercept, treatment still ongoing. At 46 months after diagnosis, the patient is in good general condition, presenting a complete response of the disease, demonstrated by a total body CT scan, performed in April 2015, completely negative.

JNK2 controls fragmentation of the Golgi complex and the G2/M transition through phosphorylation of GRASP65.

In mammalian cells, the Golgi complex is composed of stacks that are connected by membranous tubules. During G2, the Golgi complex is disassembled into isolated stacks. This process is required for entry into mitosis, indicating that the correct inheritance of the organelle is monitored by a 'Golgi mitotic checkpoint'. However, the regulation and the molecular mechanisms underlying this Golgi disassembly are still poorly understood. Here, we show that JNK2 has a crucial role in the G2-specific separation of the Golgi stacks through phosphorylation of Ser277 of the Golgi-stacking protein GRASP65 (also known as GORASP1). Inhibition of JNK2 by RNA interference or by treatment with three unrelated JNK inhibitors causes a potent and persistent cell cycle block in G2. JNK activity becomes dispensable for mitotic entry if the Golgi complex is disassembled by brefeldin A treatment or by GRASP65 depletion. Finally, measurement of the Golgi fluorescence recovery after photobleaching demonstrates that JNK is required for the cleavage of the tubules connecting Golgi stacks. Our findings reveal that a JNK2-GRASP65 signalling axis has a crucial role in coupling Golgi inheritance and G2/M transition.

Intraluminal gel ultrasound and eco-color doppler: new tools for the study of colorectal cancer in mice.

AIM: Azoxymethane (AOM) is a potent carcinogen that induces colorectal cancer in mice. Intraluminal gel ultrasound is a technique based on the injection of gel into the rectum. This technique allows the colon to be straightened and to visualize and identify tumours. MATERIALS AND METHODS: Twenty female C57Bl/6J mice were injected intraperitoneally with 10 mg/kg of AOM one time per week for six weeks. The mice were monitored by ultrasound with a Vevo 2100 system. We evaluated the tumour area and tumour vasculature with Ecocolor-Doppler (ECD). Histological examination of sacrificed mice was employed as the standard protocol. RESULTS: After 40 weeks from the injection, ultrasound analysis revealed the presence of tumours in 50% of all mice. Ex vivo analysis revealed the presence of 57% true-positives and only one false-positive. In two mice, ultrasound did not reveale the presence of tumour due to its small dimension. This indicates that ultrasound is able to detect only tumours with sizes ≥3 mm². CONCLUSION: Ultrasound is a rapid examination compared to other diagnostic techniques. It has a good sensitivity when the tumours reach the dimensions of 3 mm² or more. Intraluminal gel allows for the tumour area to be evaluated when mice are still alive, while ECD allows for vasculature of intestinal walls and colorectal tumour to be evaluated.

The dynamic optical breast imaging in the preoperative workflow of women with suspicious or malignant breast lesions: development of a new comprehensive score.

Purpose. To determine the diagnostic accuracy of DOBIComfortScan in patients with Breast Imaging Reporting suspect breast lesions (BI-RADS) 4-5 breast lesions. Materials and Methods. One-hundred and thirteen patients underwent DOBIComfortScan examination before surgery. Twelve parameters were taken into consideration to define DOBI findings. Results. Twenty-seven radical mastectomies, 47 quadrantectomies and 39 wide excisions, were performed. Overall, 65 invasive cancer, 9 in situ carcinoma and 39 nonmalignant lesions, were observed. Ten out of 12 considered parameters resulted significantly in association with histology at discriminant analysis. A summation score of 30.5 resulted to be the best cut off at ROC analysis, giving a sensitivity and specificity of 80% and 87%, respectively, and a positive predictive value of 92.2%. Finally the following DOBI-BI-RADS model was developed: malignant B5 ≥ 38 score); possibly malignant (B4 = 25 - 37 score); benign but the possibility of malignancy cannot be excluded (B3 = 20 - 24 score); benign (B2 < 20 score). Conclusion. definition of other parameters permits to improve the accuracy of this procedure. Further studies are warranted to define the potential role of DOBIComfortScan in breast cancer imaging.

Golgi complex fragmentation in G2/M transition: An organelle-based cell-cycle checkpoint.

In mammalian cells, the Golgi complex is organized into a continuous membranous system known as the Golgi ribbon, which is formed by individual Golgi stacks that are laterally connected by tubular bridges. During mitosis, the Golgi ribbon undergoes extensive fragmentation through a multistage process that is required for its correct partitioning into the daughter cells. Importantly, inhibition of this Golgi disassembly results in cell-cycle arrest at the G2 stage, suggesting that accurate inheritance of the Golgi complex is monitored by a "Golgi mitotic checkpoint." Here, we discuss the mechanisms and regulation of the Golgi ribbon breakdown and briefly comment on how Golgi partitioning may inhibit G2/M transition.

The role of Aurora-A kinase in the Golgi-dependent control of mitotic entry.

During mitosis, the Golgi complex undergoes a multi-step fragmentation process that is instrumental to its correct partitioning into the daughter cells. To prepare for this segregation, the Golgi ribbon is initially separated into individual stacks during the G2 phase of the cell cycle. Then, at the onset of mitosis, these individual stacks are further disassembled into dispersed fragments. Inhibition of this Golgi fragmentation step results in a block or delay of G2/M transition, depending on the experimental approach. Thus, correct segregation of the Golgi complex appears to be monitored by a 'Golgi mitotic checkpoint'. Using a microinjection-based approach, we recently identified the first target of the Golgi checkpoint, whereby a block of this Golgi fragmentation impairs recruitment of the mitotic kinase Aurora-A to, and its activation at, the centrosomes. Overexpression of Aurora-A can override this cell cycle block, indicating that Aurora-A is a major effector of the Golgi checkpoint. We have also shown that this block of Aurora-A recruitment to the centrosomes is not mediated by the known mechanisms of regulation of Aurora-A function. Here we discuss our findings in relation to the known functions of Aurora-A.

Gallbladder metastasis: spectrum of imaging findings.

The objective of this study is to report the diagnostic features of hematogenous gallbladder metastasis using various imaging modalities. We carried out a single-center retrospective analysis of 13 patients with gallbladder metastasis. The primary malignancy was cutaneous melanoma (11 cases), hepatocellular carcinoma (1 case), and non-Hodgkin lymphoma (1 case). All patients underwent sonography (US), with color-power-Doppler assessment in 11 cases. Contrast-enhanced US (CEUS) was performed in 8 patients, MDCT in 8, and MR imaging in 1. Four subjects studied by whole-body PET. The gallbladder lesions were first detected with US in 9 cases and with MDCT in 3 cases. The remaining patient was investigated because of hepatic fluorodeoxyglucose uptake at PET; CEUS failed to detect any liver metastasis in this subject but identified a gallbladder lesion. Typical findings included multiplicity of gallbladder vegetations, broad base, limited mural thickening, presence of contrast enhancement, absence of gallstones and gallbladder bed infiltration, presence of combined lesions within other organs. Only two patients presented an isolated location in the gallbladder and were successfully treated with surgery. Gallbladder metastasis is a rare but possible occurrence. Knowledge of the typical imaging features and careful evaluation of the gallbladder may avoid an incorrect or false negative diagnosis.

Golgi partitioning controls mitotic entry through Aurora-A kinase.

At the onset of mitosis, the Golgi complex undergoes a multistep fragmentation process that is required for its correct partitioning into the daughter cells. Inhibition of this Golgi fragmentation results in cell cycle arrest at the G2 stage, suggesting that correct inheritance of the Golgi complex is monitored by a "Golgi mitotic checkpoint." However, the molecular basis of this G2 block is not known. Here, we show that the G2-specific Golgi fragmentation stage is concomitant with centrosome recruitment and activation of the mitotic kinase Aurora-A, an essential regulator for entry into mitosis. We show that a block of Golgi partitioning impairs centrosome recruitment and activation of Aurora-A, which results in the G2 block of cell cycle progression. Overexpression of Aurora-A overrides this cell cycle block, indicating that Aurora-A is a major effector of the Golgi checkpoint. Our findings provide the basis for further understanding of the signaling pathways that coordinate organelle inheritance and cell duplication.