CD44 is overexpressed in basal-like breast cancers but is not a driver of 11p13 amplification

Klingbeil, Pamela; Natrajan, Rachael; Everitt, Gemma; Vatcheva, Radost; Marchiò, Caterina; Palacios, José; Buerger, Horst; Reis‐Filho, Jorge S.; Isacke, Clare M.

doi:10.1007/s10549-009-0380-7

Cited by 57 publications

(45 citation statements)

References 44 publications

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“…-status is associated with the basal-like or triple negative subgroups of breast cancer (11,12,14,24). Although in our study this phenotype was more common in the triple negative subgroups, no statistical significance was seen in the comparison between phenotypes and subgroups.…”

Section: Discussioncontrasting

confidence: 78%

Prognostic significance of CD24 and claudin-7 immunoexpression in ductal invasive breast cancer

et al. 2011

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Section: Discussioncontrasting

confidence: 78%

Prognostic significance of CD24 and claudin-7 immunoexpression in ductal invasive breast cancer

et al. 2011

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“…Although the majority (>80%) of microarray-defined HER2 cancers harbour HER2 gene amplification or HER2 3+ immunohistochemical expression [33], not all fall into the HER2 cluster by expression array analysis [30,33]. [42], CD44 [43] and epidermal growth factor receptor (EGFR) [36]. In a minority of cases, they harbour EGFR gene amplification [8] or aneusomy [44].…”

Section: Class Discovery Studies: Moving Away From Histopathology?mentioning

confidence: 99%

The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade

Weigelt

Baehner

Reis‐Filho

2009

The Journal of Pathology

395

355

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In the last decade, the development of microarrays and the ability to perform massively parallel gene expression analysis of human tumours were received with great excitement by the scientific community. The promise of microarrays was of apocalyptic dimensions, with some experts envisaging that it would be a matter of a few years for this technology to replace traditional clinicopathological markers in clinical practice and treatment decision-making. The replacement of histopathology by high-tech and more objective approaches to cancer diagnosis, prognostication and prediction was, at that time, a foregone conclusion. Ten years after the initial publications of translational research studies using microarrays, one cannot deny that this technology has changed the way breast cancer is perceived. It has brought the concept of breast cancer heterogeneity to the forefront of cancer research, and the fact that distinct subtypes of breast cancer are completely different diseases that affect the same anatomical site. Furthermore, it has led to the development of prognostic and predictive 'gene signatures', which are yet to be fully incorporated into clinical practice. Importantly, though, the prognostic and predictive power of microarrays has been shown to be complementary to, rather than a replacement for, traditional clinicopathological parameters. Here we endeavour to provide a fair and balanced assessment of what microarray-based gene expression analysis has taught us in the last decade and its contribution to breast cancer classification, prognostication and prediction.

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“…qPCR qPCR was performed as previously described (Klingbeil et al, 2010). Briefly, qPCR primers were purchased as assayson-demand from Applied Biosystems (Warrington, UK): Hs00164438_m1 for human ENG, Hs00161904_m1 for human SNAI2, Hs01101127_m1 for human ANGPTL4, Hs00167155_m1 for human SERPINE1 and 4310884E for glyceraldehyde-3-phosphate dehydrogenase.…”

Section: Cell Assaysmentioning

confidence: 99%

Endoglin expression in breast tumor cells suppresses invasion and metastasis and correlates with improved clinical outcome

et al. 2010

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Tumor growth factor-b (TGF-b) signaling in cancer has been implicated in growth suppression of early lesions and enhancing tumor cell invasion and metastasis. However, the cellular mechanisms that determine this signaling output in individual tumors are still largely unknown. In endothelial cells, TGF-b signaling is modulated by the TGF-b coreceptor endoglin (CD105). Here we demonstrate that endoglin is expressed in a subset of invasive breast cancers and cell lines and is subject to epigenetic silencing by gene methylation. Endoglin downregulation in non-tumorigenic MCF10A breast cells leads to the formation of abnormal acini in 3D culture, but does not promote cell migration or transformation. In contrast, in the presence of activated ErbB2, endoglin downregulation in MCF10A cells leads to enhanced invasion into a 3D matrix. Consistent with these data, ectopic expression of endoglin in MDA-MB-231 cells blocks TGF-b-enhanced cell motility and invasion and reduces lung colonization in an in vivo metastasis model. Unlike endothelial cells, endoglin does not modulate Smadmediated TGF-b signaling in breast cells but attenuates the cytoskeletal remodeling to impair cell migration and invasion. Importantly, in a large cohort of invasive breast cancers, lack of endoglin expression in the tumor cell compartment correlates with ENG gene methylation and poor clinical outcome.

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CD44 is overexpressed in basal-like breast cancers but is not a driver of 11p13 amplification

Cited by 57 publications

References 44 publications

Prognostic significance of CD24 and claudin-7 immunoexpression in ductal invasive breast cancer

Prognostic significance of CD24 and claudin-7 immunoexpression in ductal invasive breast cancer

The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade

Endoglin expression in breast tumor cells suppresses invasion and metastasis and correlates with improved clinical outcome

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