Dataset Information

Importance of RIP140 and LCoR Sub-Cellular Localization for Their Association With Breast Cancer Aggressiveness and Patient Survival.

ABSTRACT: New markers are needed to improve diagnosis and to personalize treatments for patients with breast cancer (BC). Receptor-interacting protein of 140 kDa (RIP140) and ligand-dependent corepressor (LCoR), two transcriptional co-regulators of estrogen receptors, strongly interact in BC cells. Although their role in cancer progression has been outlined in the last few years, their function in BC has not been elucidated yet. In this study, we investigated RIP140 and LCoR localization (cytoplasm vs nucleus) in BC samples from a well-characterized cohort of patients (n?=?320). RIP140 and LCoR were expressed in more than 80% of tumors, (predominantly in the cytoplasm), and the two markers were highly correlated. Expression of RIP140 and LCoR in the nucleus was negatively correlated with tumor size. Conversely, RIP140 and LCoR cytoplasmic expression strongly correlated with expression of two tumor aggressiveness markers: N-cadherin and CD133 (epithelial mesenchymal transition and cancer stem cell markers, respectively). Finally, high RIP140 nuclear expression was significantly correlated with longer overall survival, whereas high total or cytoplasmic expression of RIP140 was associated with shorter disease-free survival. Our study strongly suggests that the role of RIP140 and LCoR in BC progression could vary according to their prevalent sub-cellular localization, with opposite prognostic values for nuclear and cytoplasmic expression. The involvement in BC progression/invasiveness of cytoplasmic RIP140 could be balanced by the anti-tumor action of nuclear RIP140, thus explaining the previous contradictory findings about its role in BC.

SUBMITTER: Sixou S

PROVIDER: S-EPMC6070698 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Importance of RIP140 and LCoR Sub-Cellular Localization for Their Association With Breast Cancer Aggressiveness and Patient Survival.

Sixou Sophie S Müller Katharina K Jalaguier Stéphan S Kuhn Christina C Harbeck Nadia N Mayr Doris D Engel Jutta J Jeschke Udo U Ditsch Nina N Cavaillès Vincent V

Translational oncology 20180711 5

New markers are needed to improve diagnosis and to personalize treatments for patients with breast cancer (BC). Receptor-interacting protein of 140 kDa (RIP140) and ligand-dependent corepressor (LCoR), two transcriptional co-regulators of estrogen receptors, strongly interact in BC cells. Although their role in cancer progression has been outlined in the last few years, their function in BC has not been elucidated yet. In this study, we investigated RIP140 and LCoR localization (cytoplasm vs nuc ...[more]

PMID: 30007204

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Project description:PURPOSE:Ligand-dependent corepressor (LCoR) and receptor-interacting protein 140 (RIP140/NRIP1) play an important role in the regulation of multiple oncogenic signaling pathways and the development of cancer. LCoR and RIP140 form a nuclear complex in breast cancer cells and are of prognostic value in further prostate and cervical cancer. The purpose of this study was to analyze the regulation of these proteins in the development of cervical intraepithelial neoplasia (CIN I-III). METHODS:Immunohistochemical analysis was obtained to quantify RIP140 and LCoR expression in formalin-fixed paraffin embedded tissue sections of cervical intraepithelial neoplasia samples. Tissue (n?=?94) was collected from patients treated in the Department of Gynecology and Obstetrics, Ludwig-Maximilians-University of Munich, Germany, between 2002 and 2014. Correlations of expression levels with clinical outcome were carried out to assess for prognostic relevance in patients with CIN2 progression. Kruskal-Wallis test and Mann-Whitney U test were used for data analysis. RESULTS:Nuclear LCoR overexpression correlates significantly with CIN II progression. Nuclear RIP140 expression significantly increases and nuclear LCoR expression decreases with higher grading of cervical intraepithelial neoplasia. Cytoplasmic RIP140 expression is significantly higher in CIN III than in CIN I or CIN II. CONCLUSION:A decrease of nuclear LCoR expression in line with an increase of dedifferentiation of CIN can be observed. Nuclear LCoR overexpression correlates with CIN II progression indicating a prognostic value of LCoR in cervical intraepithelial neoplasia. Nuclear and cytoplasmic RIP140 expression increases significantly with higher grading of cervical intraepithelial neoplasia underlining its potential role in the development of pre-cancerous lesions. These findings support the relevance of LCoR and RIP140 in the tumorigenesis indicating a possible role of LCoR and RIP140 as targets for novel therapeutic approaches in cervical intraepithelial neoplasia and cervical cancer.

Project description:BackgroundThe expansion of automatic imaging technologies has created a need to be able to efficiently compare and review large sets of image data. To enable comparisons of image data between samples we need to define the normal variation within distinct images of the same sample. Even with tightly controlled experimental conditions, protein expression can vary widely between cells, and because of the difficulty in viewing and comparing large image sets this might not be observed. Here we introduce a novel methodology, iCluster, for visualizing, clustering and comparing large sub-cellular localization image sets. For each member of an image set, iCluster generates statistics that have been found to be useful in distinguishing sub-cellular localization. The statistics are mapped into two or three dimensions such as to preserve distances between the statistics vectors. The complete image set is then visualized in two or three dimensions using the coordinates so determined. The result is images that are statistically similar are spatially close in the visualization allowing for easy comparison of images that are similar and distinguishment of dissimilar images into distinct clusters.ResultsThe methodology was tested on a set of 502 previously published images containing 10 known sub-cellular localizations. The clustering of images of like type was evaluated both by examining the classes of nearest neighbors to each image and by visual inspection. In three dimensions, 3-neighbor classification accuracy was 83.2%. Visually, each class clustered well with the majority of classes localizing to distinct regions of the space. In two dimensions, 3-neighbor classification accuracy was 68.9%, though visually clustering into classes could be readily discerned. Computational expense was found to be relatively low, and sets of up to 1400 images visualized and interacted with in real time.ConclusionThe feasibility of automated spatial layout to allow comparison and discrimination of high throughput sub-cellular imaging has been demonstrated. There are many potential applications such as image database curation, semi-automated interactive classification, outlier detection and reference image comparison. By allowing the observation of the full range of imaging data available using modern microscopes these methods will provide an invaluable tool for cell biologists.

Dataset Information

Importance of RIP140 and LCoR Sub-Cellular Localization for Their Association With Breast Cancer Aggressiveness and Patient Survival.

Publications

Importance of RIP140 and LCoR Sub-Cellular Localization for Their Association With Breast Cancer Aggressiveness and Patient Survival.

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