Molecular Genomic Testing for Breast Cancer: Utility for Surgeons

Fayanju, Oluwadamilola M.; Park, Ko Un; Lucci, Anthony

doi:10.1245/s10434-017-6254-z

Cited by 22 publications

(16 citation statements)

References 39 publications

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“…EndoPredict is used to calculate the endopredict (EP) risk score, which is used along with tumor size and nodal status to calculate the EPclin score, a comprehensive risk score. [3] It can be run using either FFPE samples, tissue from the diagnostic core biopsies, or from the final surgical specimen ( 31 ). It is incorporated in the guidelines of ESMO, St Gallen’s, ASCO, and AGO ( 89 ).…”

Section: Discussionmentioning

confidence: 99%

Genomic Assays in Node Positive Breast Cancer Patients: A Review

et al. 2021

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In recent years, developments in breast cancer have allowed yet another realization of individualized medicine in the field of oncology. One of these advances is genomic assays, which are considered elements of standard clinical practice in the management of breast cancer. These assays are widely used today not only to measure recurrence risk in breast cancer patients at an early stage but also to tailor treatment as well and minimize avoidable treatment side effects. At present, genomic tests are applied extensively in node negative disease. In this article, we review the use of these tests in node positive disease, explore their ramifications on neoadjuvant chemotherapy decisions, highlight sufficiently powered recent studies emphasizing their use and review the most recent guidelines.

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Section: Discussionmentioning

confidence: 99%

Genomic Assays in Node Positive Breast Cancer Patients: A Review

et al. 2021

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“…Thus, these tests help distinguish patients who need more aggressive treatments from those for whom the current standard-of-care may suffice, reducing healthcare expenditures. Several multigene tests (MGTs) are now routinely used in the clinical setting, and have been described in previous literature [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71]. The focus of this review is on more recent and emerging technologies, and these MGTs are summarized in Table 1 and their gene/protein signatures illustrated in Figure 2.…”

Section: Gene-centered Biomarkers: Translating Molecular Complexitmentioning

confidence: 99%

“…However, Oncotype DX has recently discarded the intermediate recurrence score group. The intermediate recurrence score (RS) (initially 18 ≤ RS ≤ 30; re-classified as 11–25) in Oncotype DX had arguably been a grey area, leaving many women uncertain and concerned about their best treatment options (to omit chemotherapy or not) [29,33]. To address this issue, in 2006, began the TAILORx Study, one of the largest, randomized adjuvant BC treatment trials (in early stage, hormone-receptor–positive, HER2 negative, axillary node-negative BC patients).…”

Section: Gene-centered Biomarkers: Translating Molecular Complexitmentioning

confidence: 99%

Panoptic View of Prognostic Models for Personalized Breast Cancer Management

Saini

Mittal

Rida

et al. 2019

Cancers

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The efforts to personalize treatment for patients with breast cancer have led to a focus on the deeper characterization of genotypic and phenotypic heterogeneity among breast cancers. Traditional pathology utilizes microscopy to profile the morphologic features and organizational architecture of tumor tissue for predicting the course of disease, and is the first-line set of guiding tools for customizing treatment decision-making. Currently, clinicians use this information, combined with the disease stage, to predict patient prognosis to some extent. However, tumoral heterogeneity stubbornly persists among patient subgroups delineated by these clinicopathologic characteristics, as currently used methodologies in diagnostic pathology lack the capability to discern deeper genotypic and subtler phenotypic differences among individual patients. Recent advancements in molecular pathology, however, are poised to change this by joining forces with multiple-omics technologies (genomics, transcriptomics, epigenomics, proteomics, and metabolomics) that provide a wealth of data about the precise molecular complement of each patient’s tumor. In addition, these technologies inform the drivers of disease aggressiveness, the determinants of therapeutic response, and new treatment targets in the individual patient. The tumor architecture information can be integrated with the knowledge of the detailed mutational, transcriptional, and proteomic phenotypes of cancer cells within individual tumors to derive a new level of biologic insight that enables powerful, data-driven patient stratification and customization of treatment for each patient, at each stage of the disease. This review summarizes the prognostic and predictive insights provided by commercially available gene expression-based tests and other multivariate or clinical -omics-based prognostic/predictive models currently under development, and proposes a more inclusive multiplatform approach to tackling the challenging heterogeneity of breast cancer to individualize its management. “The future is already here—it’s just not very evenly distributed.”-William Ford Gibson

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“…The prognosis of breast cancer and therapeutic decision-making are known to depend on classic immunohistochemistry (IHC) markers, namely estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Recently, genomic assays have been used to provide information and to help in decision-making for adjuvant treatment [3]. Differential expression of various proteins has been researched to develop more efficient options for diagnosis and treatment.…”

Section: Introductionmentioning

confidence: 99%

Clinicopathological Significance of SMAD4 Expression in Breast Cancer

2019

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Purpose: SMAD4 is a member of the SMAD family and acts as a central mediator of transforming growth factor beta signaling. Little is known about SMAD4 expression and its prognostic significance in breast cancer. We evaluated the clinicopathological and prognostic significance of SMAD4 expression in breast cancer. Methods: Two hundred and fifty-five patients with invasive ductal carcinoma of the breast from 2000 to 2008 were retrospectively analyzed. We investigated SMAD4 expression using a tissue microarray-based immunohistochemical assay and evaluated the association between SMAD4 and prognosis of breast cancer. Results: High SMAD4 expression was positively associated with early stage (p= 0.009), estrogen receptor positivity (p= 0.026), and human epidermal growth factor receptor 2 negativity (p= 0.001). A significant difference in overall survival (OS) was associated with high SMAD4 expression in patients with T1 stage tumors (hazard ratio: 0.459, p= 0.024). Conclusion: High SMAD4 expression was correlated with several favorable prognostic factors and was associated with favorable OS in T1 stage breast cancer. SMAD4 in breast cancer has potential prognostic significance, and further investigations and understanding about SMAD4 expression are needed.

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Molecular Genomic Testing for Breast Cancer: Utility for Surgeons

Cited by 22 publications

References 39 publications

Genomic Assays in Node Positive Breast Cancer Patients: A Review

Genomic Assays in Node Positive Breast Cancer Patients: A Review

Panoptic View of Prognostic Models for Personalized Breast Cancer Management

Clinicopathological Significance of SMAD4 Expression in Breast Cancer

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