Triple-negative breast cancer

Stockmans, Gert; Deraedt, Karen; Wildiers, Hans; Moerman, Philippe; Paridaens, Robert

doi:10.1097/cco.0b013e328312efba

Cited by 60 publications

(54 citation statements)

References 49 publications

(58 reference statements)

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“…Textural kinetics are quantitative imaging features that describe the dynamic variation of textural features of breast lesions during contrast material uptake and can outperform standard morphologic, static texture, and kinetic intensity features in the differentiation of benign T riple-negative breast cancer has recently been identified as an important subtype owing to its prevalence in the population (10%-20% of all diagnosed breast cancer [1]), lack of options for targeted molecular therapies (2), and poor prognosis (3). Dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging is sensitive for detecting triple-negative cancer (4,5) and screening BRCA mutation carriers (4,(6)(7)(8)(9), who often develop triple-negative cancer (1)-particularly BRCA1 mutation carriers.…”

Section: Methodsmentioning

confidence: 99%

Computerized Image Analysis for Identifying Triple-Negative Breast Cancers and Differentiating Them from Other Molecular Subtypes of Breast Cancer on Dynamic Contrast-enhanced MR Images: A Feasibility Study

Agner¹,

Rosen²,

Englander³

et al. 2014

Radiology

134

125

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Purpose:To determine the feasibility of using a computer-aided diagnosis (CAD) system to differentiate among triple-negative breast cancer, estrogen receptor (ER)-positive cancer, human epidermal growth factor receptor type 2 (HER2)-positive cancer, and benign fibroadenoma lesions on dynamic contrast material-enhanced (DCE) magnetic resonance (MR) images. Materials andMethods:This is a retrospective study of prospectively acquired breast MR imaging data collected from an institutional review board-approved, HIPAAcompliant study between 2002 and 2007. Written informed consent was obtained from all patients. The authors collected DCE MR images from 65 women with 76 breast lesions who had been recruited into a larger study of breast MR imaging. The women had triple-negative (n = 21), ER-positive (n = 25), HER2-positive (n = 18), or fibroadenoma (n = 12) lesions. All lesions were classified as Breast Imaging Reporting and Data System category 4 or higher on the basis of previous imaging. Images were subject to quantitative feature extraction, feed-forward feature selection by means of linear discriminant analysis, and lesion classification by using a support vector machine classifier. The area under the receiver operating characteristic curve (A z ) was calculated for each of five lesion classification tasks involving triple-negative breast cancers. Results:For Conclusion:Triple-negative cancers possess certain characteristic features on DCE MR images that can be captured and quantified with CAD, enabling good discrimination of triple-negative cancers from non-triple-negative cancers, as well as between triple-negative cancers and benign fibroadenomas. Such CAD algorithms may provide added diagnostic benefit in identifying the highly aggressive triple-negative cancer phenotype with DCE MR imaging in high-risk women.q RSNA, 2014

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Section: Methodsmentioning

confidence: 99%

Computerized Image Analysis for Identifying Triple-Negative Breast Cancers and Differentiating Them from Other Molecular Subtypes of Breast Cancer on Dynamic Contrast-enhanced MR Images: A Feasibility Study

Agner¹,

Rosen²,

Englander³

et al. 2014

Radiology

134

125

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“…A critical feature of TNBC is its highly aggressive behavior (26,27). Based on our findings that HIC1 expression is silenced in TNBC cells, its expression was restored in MDA-231 and MDA-468 cells using a lentivirus vector.…”

Section: Effects Of Restoration Of Hic1 Expression In Tnbc Cellsmentioning

confidence: 99%

HIC1 Silencing in Triple-Negative Breast Cancer Drives Progression through Misregulation of LCN2

et al. 2014

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The tumor suppressor gene HIC1 is frequently deleted or epigenetically silenced in human cancer, where its restoration may improve cancer prognosis. Here, we report results illuminating how HIC1 silencing alters effect or signals in triple-negative breast cancer (TNBC), which are crucial for its pathogenesis. HIC1 expression was silenced only in TNBC compared with other molecular subtypes of breast cancer. Restoring HIC1 expression in TNBC cells reduced cell migration, invasion, and metastasis, whereas RNAi-mediated silencing of HIC1 in untransformed human breast cells increased their invasive capabilities. Mechanistic investigations identified the small-secreted protein lipocalin-2 (LCN2), as a critical downstream target of HIC1 in TNBC cells. Elevating LCN2 expression in cells expressing HIC1 partially rescued its suppression of cell invasion and metastasis. Notably, autocrine secretion of LCN2 induced by loss of HIC1 activated the AKT pathway through the neutrophil gelatinase-associated lipocalin receptor, which is associated with TNBC progression. Taken together, our findings revealed that the HIC1-LCN2 axis may serve as a subtype-specific prognostic biomarker, providing an appealing candidate target for TNBC therapy. Cancer Res; 74(3); 862-72. Ó2013 AACR.

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“…In accordance with current literature, [16][17][18][19] triple negative tumors proved to be a very heterogeneous class, thereby limiting their utility in predicting the outcome of single cases.…”

mentioning

confidence: 84%

Predicting breast cancer outcome: Traditional prognosticators still on center stage

Mattioli

Giordano²,

Pentimalli

2010

Cancer Biology & Therapy

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Triple-negative breast cancer

Cited by 60 publications

References 49 publications

Computerized Image Analysis for Identifying Triple-Negative Breast Cancers and Differentiating Them from Other Molecular Subtypes of Breast Cancer on Dynamic Contrast-enhanced MR Images: A Feasibility Study

Computerized Image Analysis for Identifying Triple-Negative Breast Cancers and Differentiating Them from Other Molecular Subtypes of Breast Cancer on Dynamic Contrast-enhanced MR Images: A Feasibility Study

HIC1 Silencing in Triple-Negative Breast Cancer Drives Progression through Misregulation of LCN2

Predicting breast cancer outcome: Traditional prognosticators still on center stage

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