Ki67 Index, HER2 Status, and Prognosis of Patients With Luminal B Breast Cancer

"Background Gene expression profiling of breast cancer has identified two biologically distinct estrogen receptor (ER)-positive subtypes of breast cancer: luminal A and luminal B. Luminal B tumors have higher proliferation and poorer prognosis than luminal A tumors. In this study, we developed a clinically practical immunohistochemistry assay to distinguish luminal B from luminal A tumors and investigated its ability to separate tumors according to breast cancer recurrence-free and disease-specific survival. Methods Tumors from a cohort of 357 patients with invasive breast carcinomas were subtyped by gene expression profile. Hormone receptor status, HER2 status, and the Ki67 index (percentage of Ki67-positive cancer nuclei) were determined immunohistochemically. Receiver operating characteristic curves were used to determine the Ki67 cut point to distinguish luminal B from luminal A tumors. The prognostic value of the immunohistochemical assignment for breast cancer recurrence-free and disease-specific survival was investigated with an independent tissue microarray series of 4046 breast cancers by use of Kaplan–Meier curves and multivariable Cox regression. Results Gene expression profiling classified 101 (28%) of the 357 tumors as luminal A and 69 (19%) as luminal B. The best Ki67 index cut point to distinguish luminal B from luminal A tumors was 13.25%. In an independent cohort of 4046 patients with breast cancer, 2847 had hormone receptor–positive tumors. When HER2 immunohistochemistry and the Ki67 index were used to subtype these 2847 tumors, we classified 1530 (59%, 95% confidence interval [CI] = 57% to 61%) as luminal A, 846 (33%, 95% CI = 31% to 34%) as luminal B, and 222 (9%, 95% CI = 7% to 10%) as luminal–HER2 positive. Luminal B and luminal–HER2-positive breast cancers were statistically significantly associated with poor breast cancer recurrence-free and disease-specific survival in all adjuvant systemic treatment categories. Of particular relevance are women who received tamoxifen as their sole adjuvant systemic therapy, among whom the 10-year breast cancer–specific survival was 79% (95% CI = 76% to 83%) for luminal A, 64% (95% CI = 59% to 70%) for luminal B, and 57% (95% CI = 47% to 69%) for luminal–HER2 subtypes. Conclusion Expression of ER, progesterone receptor, and HER2 proteins and the Ki67 index appear to distinguish luminal A from luminal B breast cancer subtypes.

Basal-like breast cancer defined by five biomarkers has superior prognostic value than triple-negative phenotype

Purpose: Basal-like breast cancer is associated with high grade, poor prognosis, and younger patient age. Clinically, a triple-negative phenotype definition [estrogen receptor, progesterone receptor, and human epidermal growth factor receptor (HER)-2, all negative] is commonly used to identify such cases. EGFR and cytokeratin 5/6 are readily available positive markers of basallike breast cancer applicable to standard pathology specimens. This study directly compares the prognostic significance between three- and five-biomarker surrogate panels to define intrinsic breast cancer subtypes, using a large clinically annotated series of breast tumors. Experimental Design: Four thousand forty-six invasive breast cancers were assembledinto tissuemicroarrays. Allhad staging, pathology, treatment, andoutcomeinformation;median follow-up was12.5 years. Cox regression analyses and likelihood ratio tests compared the prognostic significance for breast cancer death-specific survival (BCSS) of the twoimmunohistochemicalpanels. Results: Among3,744interpretable cases,17%werebasalusing the triple-negativedefinition(10- year BCSS, 6 7%) and 9% were basal using the five-marker method (10-year BCSS, 62%). Likelihood ratio tests ofmultivariable Coxmodelsincluding standard clinical variables show that the fivemarker panel is significantly more prognostic than the three-marker panel.The poor prognosis of triple-negative phenotype is conferred almost entirely by those tumors positive for basal markers. Among triple-negativepatients treatedwithadjuvant anthracycline-based chemotherapy, theadditionalpositive basalmarkersidentified a cohort of patients with significantly worse outcome. Conclusions:The expanded surrogate immunopanel of estrogen receptor, progesterone receptor, human HER-2, EGFR, and cytokeratin 5/6 provides a more specific definition of basal-like breast cancer that better predicts breast cancer survival

Robust Automated Tumour Segmentation on Histological and Immunohistochemical Tissue Images

Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification

Failure patterns and survival outcomes in triple negative breast cancer (TNBC): a 15 year comparison of 448 non-Hispanic black and white women

Purpose: Triple negative breast cancer (TNBC) is a distinct subtype of breast cancer with unique pathologic, molecular and clinical behavior. It occurs more frequently in young blacks and has been reported to have a shorter disease-free interval. We undertook this study to analyze the demographic characteristics, failure patterns, and survival outcomes in this disease. Methods: A total of 448 non-Hispanic black and white women were identified over a 15 year period from 1996 to 2011. Demographic and clinical information including age, race, menopausal status, stage, tumor characteristics, and treatments were collected. Fisher’s exact test and multivariable Cox regression were used to compare failure patterns and survival outcomes between races. Results: 49 % (n = 223) were black. 59 % patients were between 41 and 60 years, with 18 % ≤40 years. 57 % were premenopausal and 89 % had grade 3 tumors. Stage II (47 %) was most frequent stage at diagnosis followed by stage III (28 %). 32 % had lymphovascular invasion. Adjusting for age, stage, and grade, there was no difference in survival outcomes (OS, DFS, LFFS, and DFFS) between the two races. 62 (14 %) patients failed locally either in ipsilateral breast or chest wall, and 19 (4 %) failed in the regional lymphatics. Lung (18 %) was the most frequent distant failure site with <12 % each failing in brain, liver and bones. Conclusion: Failure patterns and survival outcomes did not differ by race in this large collection of TNBC cases. Lung was the predominate site of distant failure followed by brain, bone, and liver. Few patients failed in the regional lymphatics

MiR-34b is associated with clinical outcome in triple-negative breast cancer patients

<p>Abstract</p> <p>Background</p> <p>Breast cancer is the most common malignancy with the highest incidence rates among women worldwide. Triple-negative breast cancer (TNBC) represents the major phenotype of basal-like molecular subtype of breast cancer, characterized by higher incidence in young women and a very poor prognosis. MicroRNAs (miRNAs) are small non-coding RNAs playing significant role in the pathogenesis of many cancers including breast cancer. Therefore, miRNAs are also potential prognostic and/or predictive biomarkers in triple-negative breast cancer patients.</p> <p>Methods</p> <p>Thirty-nine TNBC patients with available formalin-fixed paraffin-embedded (FFPE) tissues were enrolled in the study. MiR-34a, miR-34b, and miR-34c were analyzed using qRT-PCR and correlated to clinico-pathological features of TNBC patients.</p> <p>Results</p> <p>Expression levels of miR-34b significantly correlate with disease free survival (DFS) (<it>p </it>= 0.0020, log-rank test) and overall survival (OS) (<it>p </it>= 0.0008, log-rank test) of TNBC patients. No other significant associations between miR-34a, miR-34b, and miR-34c with available clinical pathological data were observed.</p> <p>Conclusions</p> <p>MiR-34b expression negatively correlates with disease free survival and overall survival in TNBC patients. Thus, miR-34b may present a new promising prognostic biomarker in TNBC patients, but independent validations are necessary.</p

Glycoprotein analysis using protein microarrays and mass spectrometry

Protein glycosylation plays an important role in a multitude of biological processes such as cell–cell recognition, growth, differentiation, and cell death. It has been shown that specific glycosylation changes are key in disease progression and can have diagnostic value for a variety of disease types such as cancer and inflammation. The complexity of carbohydrate structures and their derivatives makes their study a real challenge. Improving the isolation, separation, and characterization of carbohydrates and their glycoproteins is a subject of increasing scientific interest. With the development of new stationary phases and molecules that have affinity properties for glycoproteins, the isolation and separation of these compounds have advanced significantly. In addition to detection with mass spectrometry, the microarray platform has become an essential tool to characterize glycan structure and to study glycosylation-related biological interactions, by using probes as a means to interrogate the spotted or captured glycosylated molecules on the arrays. Furthermore, the high-throughput and reproducible nature of microarray platforms have been highlighted by its extensive applications in the field of biomarker validation, where a large number of samples must be analyzed multiple times. This review covers a brief survey of the other experimental methodologies that are currently being developed and used to study glycosylation and emphasizes methodologies that involve the use of microarray platforms. This review describes recent advances in several options of microarray platforms used in glycoprotein analysis, including glycoprotein arrays, glycan arrays, lectin arrays, and antibody/lectin arrays. The translational use of these arrays in applications related to characterization of cells and biomarker discovery is also included. © 2010 Wiley Periodicals, Inc., Mass Spec Rev 29:830–844, 2010Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77969/1/20269_ftp.pd