Optimizing the Use of Gene Expression Profiling in Early-Stage Breast Cancer

Kim, Hyun-seok; Umbricht, Christopher B.; Illei, Peter B.; Cimino‐Mathews, Ashley; Cho, Soonweng; Chowdhury, Nivedita; Figueroa-Magalhães, Maria Cristina; Pesce, Catherine; Jeter, Stacie C.; Mylander, Charles; Rosman, Martin; Tafra, Lorraine; Turner, Bradley M.; Jensen, Tyler A.; Miller, Dylan V.; Armstrong, Deborah K.; Connolly, Roisín M.; Fetting, John H.; Miller, Robert S.; Park, Ben Ho; Stearns, Vered; Visvanathan, Kala; Wolff, Antonio C.; Cope, Leslie

doi:10.1200/jco.2016.67.7195

Cited by 52 publications

(60 citation statements)

References 30 publications

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“…There are some inexpensive statistical prognostic models that are based on histopathological characteristics, such as ER, PR, HER2, and Ki‐67. Examples include the Breast Cancer Recurrence Score Estimator, Memorial Sloan Kettering Simplified Score, the Magee equations, and IHC4 . Our study reaffirms the importance of PR.…”

Section: Discussionsupporting

confidence: 73%

Prognostic Value of the Progesterone Receptor by Subtype in Patients with Estrogen Receptor-Positive, HER-2 Negative Breast Cancer

et al. 2018

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An absent progesterone receptor (PR) predicts a worse outcome in women treated for an estrogen receptor-positive, human epidermal growth factor receptor 2 negative breast cancer. As low proliferative tumors lacking PR are now also classified high risk, the prognostic value of PR across risk groups was studied. Despite a negative test for interaction of the prognostic value of PR by tumor grade, the magnitude of an absent PR on breast cancer relapse is much larger in high than in low proliferative breast cancers.

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Section: Discussionsupporting

confidence: 73%

Prognostic Value of the Progesterone Receptor by Subtype in Patients with Estrogen Receptor-Positive, HER-2 Negative Breast Cancer

et al. 2018

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“…Based on the latest results of TAILORx clinical trial [20], all patients >50 years of age with an RS 0‐25 could get no benefit from chemotherapy with no relationship with the clinical risk, so this variable was used for only risk stratification in younger patients ≤50 years of age. Considering the prognostic and predictive potential of the Ki‐67 index [26] and that the Ki‐67 index is widely used in many published tools [11‐13], the Ki‐67 index was used to develop the IHC3 model. Conversely, the Ki‐67 index was not included in Orucevic et al.’s nomogram, which might be a reason for its relatively low sensitivity for predicting high‐risk (RS 26‐100) patients.…”

Section: Discussionmentioning

confidence: 99%

“…Nevertheless, the 21‐gene genomic assay is not available and affordable worldwide, particularly in developing countries. In the past 10 years, several multivariable models have been integrated into traditional pathological information including tumor size, tumor histologic grade, the expression of estrogen receptor (ER), progesterone receptor (PR), and HER2, and Ki‐67 index to predict tumor recurrence and replace the RS [10‐14]. Most recurrence predictive models are mathematical equations (e.g., Cuzick et al.’s IHC4 score [10] and Turner et al.’s Magee [11] models) that are available online.…”

Section: Introductionmentioning

confidence: 99%

Ki‐67 index, progesterone receptor expression, histologic grade and tumor size in predicting breast cancer recurrence risk: A consecutive cohort study

Zhang

Zhou

Mao

et al. 2020

Cancer Communications

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Background:The 21-gene recurrence score (RS) assay has been recommended by major guidelines for treatment decision in hormone receptor (HR)-positive early breast cancer (EBC). However, the genomic assay is not accessible and affordable worldwide. Alternatively, an increasing number of studies have shown that traditional immunohistochemistry (IHC) can partially or even completely replace the role of the 21-gene genomic assay. Here, we developed and validated a predictive model (IHC3 model) combining the Ki-67 index, progesterone receptor (PR) expression, histologic grade, and tumor size to predict the recurrence risk of HR-positive EBC. Methods: The data from 389 patients (development set) with HR-positive, human epidermal growth factor receptor 2-negative, lymph node non-metastasized invasive breast cancer were used to construct the IHC3 model based on the Surexam ® 21gene RS and the TAILORx clinical trial criteria. An additional 146 patients with the same characteristics constituted the validation set. The predictive accuracy of the IHC3 model was compared with that of Orucevic et al.'s nomogram. Invasive diseasefree survival (IDFS) was analyzed in the IHC3 predictive low-recurrence risk (pLR) group and the predictive high-recurrence risk (pHR) group. The Pearson chi-square test, Fisher exact test, and log-rank test were used for analysis. Results: The pLR and pHR group could be easily stratified using the decision tree model without network dependence. The accuracies of the IHC3 model were 86.1% in the development set and 87.7% in the validation set. The predictive accuracy of the IHC3 model and Orucevic et al.'s nomogram for the whole cohort was 86.5% and 86.9%, respectively. After a 52-month of median follow-up, a significant difference Abbreviations: ALND, axillary lymph node dissection; CART, classification and regression trees; EBC, early breast cancer; ER, estrogen receptor; FISH, fluorescence in situ hybridization; HER2, human epidermal growth factor receptor 2; HR, hormone receptor; IDC, invasive ductal carcinoma; IDFS, invasive disease-free survival; IHC, immunohistochemistry; ILC, invasive lobular carcinoma; NPV, negative predictive value; pHR, predictive high-recurrence risk; pLR, predictive low-recurrence risk; PPV, positive predictive value; PR, progesterone receptor; RS, recurrence score; SERM, selective estrogen receptor modulator; SLNB, sentinel lymph node biopsy.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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“…This leads to preselecting patients for the uPA/PAI‐1 testing before the final grading and lymph node status are known, whereas the patients for EPclin testing are chosen after the conclusive report. In consequence, uPA/PAI‐1 tests are run in patients who do not fulfill recommendations and fall into Stage III‐IV group or are node positive, when the focus of prognostic tests should be put on the intermediate‐risk group for which they have been validated . The tissue for uPA/PAI‐1 should be collected at a safe distance from biopsy defect to avoid false positive results due to tissue injury.…”

Section: Discussionmentioning

confidence: 99%

EndoPredict versus uPA/PAI‐1 in breast cancer: Comparison of markers and association with clinicopathological parameters

et al. 2019

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We retrospectively investigated concordance of EndoPredict (EPclin) with urokinase plasminogen activator and plasminogen activator inhibitor-1 (uPA/PAI-1) in 72 breast cancer patients and compared the results with grading, molecular subtype and chemotherapy recommendation. Compared to uPA/PAI-1, EPclin proved to be more conservative concerning correlation with clinicopathological parameters and was significantly associated with the recommendation of adjuvant chemotherapy. K E Y W O R D S breast cancer, prognosis, proteases | 451 JAKUBOWICZ et Al. was 57.5 years. The patients were submitted to lumpectomy or mastectomy in Augsburg at the Klinikum Augsburg, Josefinum Hospital or Diakonissen Hospital between the year 2011 and 2016. The information about chemotherapy was attained from the medical records of interdisciplinary tumor conference reports of Klinikum Augsburg or from the clinical and population-based cancer registry Augsburg. Recommendation concerning adjuvant chemotherapy was correlated with uPA/PAI-1 and EPclin results. The uPA/PAI-1 testing was performed in Klinikum Augsburg. Representative tumor tissue was obtained according to protocol as a part of routine gross pathology examination. The sample was submitted for evaluation with the use of commercial enzyme-linked immune sorbent assay (ELISA) test (Femtelle Test (EF 899), Sekisui Diagnostics, Stamford, CT). The test was conducted according to the manufacturer's protocol as described before. 9 The levels of uPA and PAI-1 were expressed in nanograms per milligram (ng/mg) of tumor protein. The cut-off-level for uPA and PAI-1 were 3 ng/mg protein and 14 ng/mg protein respectively. The specimen was preserved in 10% formaldehyde and processed into FFPE tissue, sectioned and stained with hematoxylinand-eosin (HE). For immunohistochemical analysis, paraffin sections measuring approximately 3 μm were processed in streptavidin-biotin-peroxidase and incubated with estrogen, progesterone, ki67, How to cite this article: Jakubowicz E, Martin B, Hoffmann R, et al. EndoPredict versus uPA/PAI-1 in breast cancer: Comparison of markers and association with clinicopathological parameters. Breast J. 2019;25:450-454.

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Optimizing the Use of Gene Expression Profiling in Early-Stage Breast Cancer

Cited by 52 publications

References 30 publications

Prognostic Value of the Progesterone Receptor by Subtype in Patients with Estrogen Receptor-Positive, HER-2 Negative Breast Cancer

Prognostic Value of the Progesterone Receptor by Subtype in Patients with Estrogen Receptor-Positive, HER-2 Negative Breast Cancer

Ki‐67 index, progesterone receptor expression, histologic grade and tumor size in predicting breast cancer recurrence risk: A consecutive cohort study

EndoPredict versus uPA/PAI‐1 in breast cancer: Comparison of markers and association with clinicopathological parameters

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