Effects of oestrogens and anti-oestrogens on normal breast tissue from women bearing BRCA1 and BRCA2 mutations

There is considerable interest in whether anti-oestrogens can be used to prevent breast cancer in women bearing mutations in the BRCA1 and BRCA2 genes. The effects of oestradiol (E2), tamoxifen (TAM) and fulvestrant (FUL) on proliferation and steroid receptor expression were assessed in normal breast epithelium taken from women at varying risks of breast cancer and implanted into athymic nude mice, which were treated with E2 in the presence and absence of TAM or FUL. Tissue samples were taken at various time points thereafter for assessment of proliferative activity and expression of oestrogen and progesterone receptors (ERα and PgR) by immunohistochemistry. Oestradiol increased proliferation in the breast epithelium from women carrying mutations in the BRCA1/2 genes, those otherwise at increased risk and those at population risk of breast cancer. This increase was reduced by both TAM and FUL in all risk groups. In the absence of E2, PgR expression was reduced in all risk groups but significantly more so in the BRCA-mutated groups. Subsequent E2 treatment caused a rapid, complete induction of PgR expression in the population-risk group but not in the high-risk or BRCA-mutated groups in which PgR induction was significantly delayed. These data suggest that the mechanisms by which E2 induces breast epithelial PgR expression are impaired in BRCA1/2 mutation carriers, whereas those regulating proliferation remain intact. We conclude that early anti-oestrogen treatment should prevent breast cancer in very high-risk women

Differential Modulation of Retinal Degeneration by Ccl2 and Cx3cr1 Chemokine Signalling

Microglia and macrophages are recruited to sites of retinal degeneration where local cytokines and chemokines determine protective or neurotoxic microglia responses. Defining the role of Ccl2-Ccr2 and Cx3cl1-Cx3cr1 signalling for retinal pathology is of particular interest because of its potential role in age-related macular degeneration (AMD). Ccl2, Ccr2, and Cx3cr1 signalling defects impair macrophage trafficking, but have, in several conflicting studies, been reported to show different degrees of age-related retinal degeneration. Ccl2/Cx3cr1 double knockout (CCDKO) mice show an early onset retinal degeneration and have been suggested as a model for AMD. In order to understand phenotypic discrepancies in different chemokine knockout lines and to study how defects in Ccl2 and/or Cx3cr1 signalling contribute to the described early onset retinal degeneration, we defined primary and secondary pathological events in CCDKO mice. To control for genetic background variability, we compared the original phenotype with that of single Ccl2, Cx3cr1 and Ccl2/Cx3cr1 double knockout mice obtained from backcrosses of CCDKO with C57Bl/6 mice. We found that the primary pathological event in CCDKO mice develops in the inferior outer nuclear layer independently of light around postnatal day P14. RPE and vascular lesions develop secondarily with increasing penetrance with age and are clinically similar to retinal telangiectasia not to choroidal neovascularisation. Furthermore, we provide evidence that a third autosomal recessive gene causes the degeneration in CCDKO mice and in all affected re-derived lines and subsequently demonstrated co-segregation of the naturally occurring RD8 mutation in the Crb1 gene. By comparing CCDKO mice with re-derived CCl2−/−/Crb1Rd8/RD8, Cx3cr1−/−/Crb1Rd8/RD8 and CCl2−/−/Cx3cr1−/−/Crb1Rd8/RD8 mice, we observed a differential modulation of the retinal phenotype by genetic background and both chemokine signalling pathways. These findings indicate that CCDKO mice are not a model of AMD, but a model for an inherited retinal degeneration that is differentially modulated by Ccl2-Ccr2 and Cx3cl1-Cx3cr1 chemokine signalling

Method: automatic segmentation of mitochondria utilizing patch classification, contour pair classification, and automatically seeded level sets

<p>Abstract</p> <p>Background</p> <p>While progress has been made to develop automatic segmentation techniques for mitochondria, there remains a need for more accurate and robust techniques to delineate mitochondria in serial blockface scanning electron microscopic data. Previously developed texture based methods are limited for solving this problem because texture alone is often not sufficient to identify mitochondria. This paper presents a new three-step method, the Cytoseg process, for automated segmentation of mitochondria contained in 3D electron microscopic volumes generated through serial block face scanning electron microscopic imaging. The method consists of three steps. The first is a random forest patch classification step operating directly on 2D image patches. The second step consists of contour-pair classification. At the final step, we introduce a method to automatically seed a level set operation with output from previous steps.</p> <p>Results</p> <p>We report accuracy of the Cytoseg process on three types of tissue and compare it to a previous method based on Radon-Like Features. At step 1, we show that the patch classifier identifies mitochondria texture but creates many false positive pixels. At step 2, our contour processing step produces contours and then filters them with a second classification step, helping to improve overall accuracy. We show that our final level set operation, which is automatically seeded with output from previous steps, helps to smooth the results. Overall, our results show that use of contour pair classification and level set operations improve segmentation accuracy beyond patch classification alone. We show that the Cytoseg process performs well compared to another modern technique based on Radon-Like Features.</p> <p>Conclusions</p> <p>We demonstrated that texture based methods for mitochondria segmentation can be enhanced with multiple steps that form an image processing pipeline. While we used a random-forest based patch classifier to recognize texture, it would be possible to replace this with other texture identifiers, and we plan to explore this in future work.</p

Upper extremity impairments in women with or without lymphedema following breast cancer treatment

Breast-cancer-related lymphedema affects ∼25% of breast cancer (BC) survivors and may impact use of the upper limb during activity. The purpose of this study is to compare upper extremity (UE) impairment and activity between women with and without lymphedema after BC treatment. 144 women post BC treatment completed demographic, symptom, and Disability of Arm-Shoulder-Hand (DASH) questionnaires. Objective measures included Purdue pegboard, finger-tapper, Semmes-Weinstein monofilaments, vibration perception threshold, strength, range of motion (ROM), and volume. Women with lymphedema had more lymph nodes removed (p &lt; .001), more UE symptoms (p &lt; .001), higher BMI (p = .041), and higher DASH scores (greater limitation) (p &lt; .001). For all participants there was less strength (elbow flexion, wrist flexion, grip), less shoulder ROM, and decreased sensation at the medial upper arm (p &lt; .05) in the affected UE. These differences were greater in women with lymphedema, particularly in shoulder abduction ROM (p &lt; .05). Women with lymphedema had bilaterally less elbow flexion strength and shoulder ROM (p &lt; .05). Past diagnosis of lymphedema, grip strength, shoulder abduction ROM, and number of comorbidities contributed to the variance in DASH scores (R 2 of 0.463, p &lt; .001). UE impairments are found in women following treatment for BC. Women with lymphedema have greater UE impairment and limitation in activities than women without. Many of these impairments are amenable to prevention measures or treatment, so early detection by health care providers is essential

A mechanically active heterotypic E-cadherin/N-cadherin adhesion enables fibroblasts to drive cancer cell invasion

Cancer-associated fibroblasts (CAFs) promote tumour invasion and metastasis. We show that CAFs exert a physical force on cancer cells that enables their collective invasion. Force transmission is mediated by a heterophilic adhesion involving N-cadherin at the CAF membrane and E-cadherin at the cancer cell membrane. This adhesion is mechanically active; when subjected to force it triggers β-catenin recruitment and adhesion reinforcement dependent on α-catenin/vinculin interaction. Impairment of E-cadherin/N-cadherin adhesion abrogates the ability of CAFs to guide collective cell migration and blocks cancer cell invasion. N-cadherin also mediates repolarization of the CAFs away from the cancer cells. In parallel, nectins and afadin are recruited to the cancer cell/CAF interface and CAF repolarization is afadin dependent. Heterotypic junctions between CAFs and cancer cells are observed in patient-derived material. Together, our findings show that a mechanically active heterophilic adhesion between CAFs and cancer cells enables cooperative tumour invasion

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

A model species for agricultural pest genomics: the genome of the Colorado potato beetle, Leptinotarsa decemlineata (Coleoptera: Chrysomelidae)

The Colorado potato beetle is one of the most challenging agricultural pests to manage. It has shown a spectacular ability to adapt to a variety of solanaceaeous plants and variable climates during its global invasion, and, notably, to rapidly evolve insecticide resistance. To examine evidence of rapid evolutionary change, and to understand the genetic basis of herbivory and insecticide resistance, we tested for structural and functional genomic changes relative to other arthropod species using genome sequencing, transcriptomics, and community annotation. Two factors that might facilitate rapid evolutionary change include transposable elements, which comprise at least 17% of the genome and are rapidly evolving compared to other Coleoptera, and high levels of nucleotide diversity in rapidly growing pest populations. Adaptations to plant feeding are evident in gene expansions and differential expression of digestive enzymes in gut tissues, as well as expansions of gustatory receptors for bitter tasting. Surprisingly, the suite of genes involved in insecticide resistance is similar to other beetles. Finally, duplications in the RNAi pathway might explain why Leptinotarsa decemlineata has high sensitivity to dsRNA. The L. decemlineata genome provides opportunities to investigate a broad range of phenotypes and to develop sustainable methods to control this widely successful pest