Rakha EA, Reis-Filho JS, Baehner F, et al. Breast cancer prognostic classification in the molecular era: the role of histological grade. Breast Cancer Res.12:207

Department of Histopathology, Nottingham City Hospital NHS Trust, Nottingham University, Nottingham, UK.
Breast cancer research: BCR (Impact Factor: 5.49). 07/2010; 12(4):207. DOI: 10.1186/bcr2607
Source: PubMed


Breast cancer is a heterogeneous disease with varied morphological appearances, molecular features, behavior, and response to therapy. Current routine clinical management of breast cancer relies on the availability of robust clinical and pathological prognostic and predictive factors to support clinical and patient decision making in which potentially suitable treatment options are increasingly available. One of the best-established prognostic factors in breast cancer is histological grade, which represents the morphological assessment of tumor biological characteristics and has been shown to be able to generate important information related to the clinical behavior of breast cancers. Genome-wide microarray-based expression profiling studies have unraveled several characteristics of breast cancer biology and have provided further evidence that the biological features captured by histological grade are important in determining tumor behavior. Also, expression profiling studies have generated clinically useful data that have significantly improved our understanding of the biology of breast cancer, and these studies are undergoing evaluation as improved prognostic and predictive tools in clinical practice. Clinical acceptance of these molecular assays will require them to be more than expensive surrogates of established traditional factors such as histological grade. It is essential that they provide additional prognostic or predictive information above and beyond that offered by current parameters. Here, we present an analysis of the validity of histological grade as a prognostic factor and a consensus view on the significance of histological grade and its role in breast cancer classification and staging systems in this era of emerging clinical use of molecular classifiers.

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    • "On the one hand, G2 tumors were not considered in our previous analyses, thus circumventing the risk of overfitting the data because of the selection of candidate intmiRNAs . On the other, G2 tumors represent a heterogeneous category, composed of tumors with varying degrees of aggressiveness (Gnant et al., 2011; Ivshina et al., 2006; Rakha et al., 2010; Sotiriou et al., 2006). An independent cohort of 95 G2 tumors was profiled for miR-483-3p/5p, miR-342-3p and miR-1266 expression (Table S8B). "
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    ABSTRACT: Around 50% of all human microRNAs reside within introns of coding genes and are usually co-transcribed. Gene expression datasets, therefore, should contain a wealth of miRNA-relevant latent information, exploitable for many basic and translational research aims. The present study was undertaken to investigate this possibility. We developed an in silico approach to identify intronic-miRNAs relevant to breast cancer, using public gene expression datasets. This led to the identification of a miRNA signature for aggressive breast cancer, and to the characterization of novel roles of selected miRNAs in cancer-related biological phenotypes. Unexpectedly, in a number of cases, expression regulation of the intronic-miRNA was more relevant than the expression of their host gene. These results provide a proof of principle for the validity of our intronic miRNA mining strategy, which we envision can be applied not only to cancer research, but also to other biological and biomedical fields. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
    Full-text · Article · Oct 2014 · Molecular Oncology
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    • "Many studies have evaluated combinations of different parameters in order to develop a prognostic profile or prognostic index [1-4,6-12,14,15]. "
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    ABSTRACT: Background Prognosis and treatment of patients with breast carcinoma of no special type (NST) is dependent on a few established parameters, such as tumor size, histological grade, lymph node stage, expression of estrogen receptor, progesterone receptor, and HER-2/neu, and proliferation index. The original Nottingham Prognostic Index (NPI) employs a three-tiered classification system that stratifies patients with breast cancer into good, moderate, and poor prognostic groups. The aim of our study was to use robust immunohistochemical methodology for determination of ER, PR, HER-2/neu, Ki-67, p53, and Bcl-2, and to observe differences in the expression of these markers when patients are stratified according to the original, three-tiered Nottingham Prognostic Index. Methods Paraffin blocks from 120 patients diagnosed with breast carcinoma, NST, were retrieved from our archive. Cases included in the study were female patients previously treated with modified radical mastectomy and axillary dissection. Results Our study demonstrates that expression of markers of good prognosis, such as ER, PR, and Bcl-2, is seen with higher frequency in good and moderate NPI groups. In contrast, overexpression of HER-2/neu, a marker of adverse prognosis, is more frequent in moderate and poor NPI groups. High proliferation index, as measured by Ki-67, is seen in moderate and poor NPI groups, whereas low proliferation index is seen in good NPI groups. Conclusions These data confirm that the original, three-tiered NPI statistically correlates with the expression of prognostic immunohistochemical markers in breast carcinoma NST.
    Full-text · Article · Aug 2014 · World Journal of Surgical Oncology
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    • "However, the molecular mechanism of the growth and development of breast cancer remains unclear. Clinically, the tumour differentiation grade, that is, the histological grade based on tumour cell mitosis, cell differentiation, and nuclear pleomorphism, is an indicator of disease aggressiveness and an independent prognostic biomarker (Rakha et al, 2010). Currently, three important receptors, that is, oestrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (Her2), are established biomarkers in common clinical use as disease status indicators and therapeutic targets (Jordan and Morrow, 1999; Gianni et al, 2010; Lv et al, 2013). "
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    ABSTRACT: Background: Myosin X (MYO10) was recently reported to promote tumour invasion by transporting integrins to filopodial tips in breast cancer. However, the role of MYO10 in tumours remains poorly defined. Here, we report that MYO10 is required in invadopodia to mediate invasive growth and extracellular matrix degradation, which depends on the binding of MYO10's pleckstrin homology domain to PtdIns(3,4,5)P3. Methods: The expression of MYO10 and its associations with clinicopathological and biological factors were examined in breast cancer cells and breast cancer specimens (n=120). Cell migration and invasion were investigated after the silencing of MYO10. The ability of cells to form invadopodia was studied using a fluorescein isothiocyanate-conjugated gelatin degradation assay. A mouse model was established to study tumour invasive growth and metastasis in vivo. Results: Elevated MYO10 levels were correlated with oestrogen receptor status, progesterone receptor status, poor differentiation, and lymph node metastasis. Silencing MYO10 reduced cell migration and invasion. Invadopodia were responsible for MYO10's role in promoting invasion. Furthermore, decreased invasive growth and lung metastasis were observed in the MYO10-silenced nude mouse model. Conclusions: Our findings suggest that elevated MYO10 expression increases the aggressiveness of breast cancer; this effect is dependent on the involvement of MYO10 in invadopodial formation.
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