Biomedical subjects

Maggie C U Cheang

Publications and source records attributed to Maggie C U Cheang.

11 recordsLinked to original sources

PubMed2006

Immunohistochemical detection using the new rabbit monoclonal antibody SP1 of estrogen receptor in breast cancer is superior to mouse monoclonal antibody 1D5 in predicting survival.

PURPOSE: Estrogen receptor (ER) expression predicts improved breast cancer-specific survival and reduced risk of recurrence and is targeted in breast cancer therapy. A high-quality antibody to identify ER-positive patients plays an important role in clinical decision making for women with breast cancer. This study evaluates immunohistochemistry using two anti-ER antibodies, a new rabbit monoclonal antibody (SP1) and the mouse monoclonal antibody (1D5), in relation to biochemical ER assay results and clinical data on survival and adjuvant systemic therapy. PATIENTS AND METHODS: A population-based tissue microarray series of 4,150 invasive breast cancers was constructed. All patients had staging, pathology, treatment, and follow-up information. The median follow-up was 12.4 years and the median age at diagnosis 60 years. Survival analysis and log-rank tests were used to evaluate the prognostic value of ER status and correlations with clinical data. RESULTS: Among the 4,105 samples interpretable for both antibodies, SP1 detected ER positivity in 69.5% and 1D5 in 63.1% of cases. Both monoclonal antibodies are demonstrated to be good prognostic indictors for breast cancer-specific and relapse-free survival. In multivariate analysis, including age, tumor size, grade, and lymphovascular and nodal status, SP1 was a better independent prognostic factor than 1D5. Among patients with discrepant ER results, the 8% of patients who were SP1 positive/1D5 negative showed good outcomes, and the 2% SP1-negative/1D5 positive had poor outcomes. Maintaining the same 92% specificity and 98% positive predictive value, SP1 is 8% more sensitive than 1D5 using biochemical assay as gold standard. CONCLUSION: SP1 represents an improved standard for ER immunohistochemistry assessment in breast cancer.

Animals↗

PubMed2006

Novel prognostic immunohistochemical biomarker panel for estrogen receptor-positive breast cancer.

PURPOSE: Patients with breast cancer experience progression and respond to treatment in diverse ways, but prognostic and predictive tools for the oncologist are limited. We have used gene expression data to guide the production of hundreds of novel antibody reagents to discover novel diagnostic tools for stratifying carcinoma patients. PATIENTS AND METHODS: One hundred forty novel and 23 commercial antisera, selected on their ability to differentially stain tumor samples, were used to stain paraffin blocks from a retrospective breast cancer cohort. Cox proportional hazards and regression tree analysis identified minimal panels of reagents able to predict risk of recurrence. We tested the prognostic association of these prospectively defined algorithms in two independent cohorts. RESULTS: In both validation cohorts, the Kaplan-Meier estimates of recurrence confirmed that both the Cox model using five reagents (p53, NDRG1, CEACAM5, SLC7A5, and HTF9C) and the regression tree model using six reagents (p53, PR, Ki67, NAT1, SLC7A5, and HTF9C) distinguished estrogen receptor (ER)-positive patients with poor outcomes. The Cox model was superior and distinguished patients with poor outcomes from patients with good or moderate outcomes with a hazard ratio of 2.21 (P = .0008) in validation cohort 1 and 1.88 (P = .004) in cohort 2. In multivariable analysis, the calculated risk of recurrence was independent of stage, grade, and lymph node status. A model proposed for ER-negative patients failed validation in the independent cohorts. CONCLUSION: A panel of five antibodies can significantly improve on traditional prognosticators in predicting outcome for ER-positive breast cancer patients.

Algorithms↗

PubMed2006

Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study.

CONTEXT: Gene expression analysis has identified several breast cancer subtypes, including basal-like, human epidermal growth factor receptor-2 positive/estrogen receptor negative (HER2+/ER-), luminal A, and luminal B. OBJECTIVES: To determine population-based distributions and clinical associations for breast cancer subtypes. DESIGN, SETTING, AND PARTICIPANTS: Immunohistochemical surrogates for each subtype were applied to 496 incident cases of invasive breast cancer from the Carolina Breast Cancer Study (ascertained between May 1993 and December 1996), a population-based, case-control study that oversampled premenopausal and African American women. Subtype definitions were as follows: luminal A (ER+ and/or progesterone receptor positive [PR+], HER2-), luminal B (ER+ and/or PR+, HER2+), basal-like (ER-, PR-, HER2-, cytokeratin 5/6 positive, and/or HER1+), HER2+/ER- (ER-, PR-, and HER2+), and unclassified (negative for all 5 markers). MAIN OUTCOME MEASURES: We examined the prevalence of breast cancer subtypes within racial and menopausal subsets and determined their associations with tumor size, axillary nodal status, mitotic index, nuclear pleomorphism, combined grade, p53 mutation status, and breast cancer-specific survival. RESULTS: The basal-like breast cancer subtype was more prevalent among premenopausal African American women (39%) compared with postmenopausal African American women (14%) and non-African American women (16%) of any age (P<.001), whereas the luminal A subtype was less prevalent (36% vs 59% and 54%, respectively). The HER2+/ER- subtype did not vary with race or menopausal status (6%-9%). Compared with luminal A, basal-like tumors had more TP53 mutations (44% vs 15%, P<.001), higher mitotic index (odds ratio [OR], 11.0; 95% confidence interval [CI], 5.6-21.7), more marked nuclear pleomorphism (OR, 9.7; 95% CI, 5.3-18.0), and higher combined grade (OR, 8.3; 95% CI, 4.4-15.6). Breast cancer-specific survival differed by subtype (P<.001), with shortest survival among HER2+/ER- and basal-like subtypes. CONCLUSIONS: Basal-like breast tumors occurred at a higher prevalence among premenopausal African American patients compared with postmenopausal African American and non-African American patients in this population-based study. A higher prevalence of basal-like breast tumors and a lower prevalence of luminal A tumors could contribute to the poor prognosis of young African American women with breast cancer.

Adult↗

PubMed2006

Disruption of the Y-box binding protein-1 results in suppression of the epidermal growth factor receptor and HER-2.

The overexpression of the epidermal growth factor receptor (EGFR) and HER-2 underpin the growth of aggressive breast cancer; still, it is unclear what governs the regulation of these receptors. Our laboratories recently determined that the Y-box binding protein-1 (YB-1), an oncogenic transcription/translation factor, induced breast tumor cell growth in monolayer and in soft agar. Importantly, mutating YB-1 at Ser(102), which resides in the DNA-binding domain, prevented growth induction. We reasoned that the underlying cause for growth attenuation by YB-1(Ser(102)) is through the regulation of EGFR and/or HER-2. The initial link between YB-1 and these receptors was sought by screening primary tumor tissue microarrays. We determined that YB-1 (n = 389 cases) was positively associated with EGFR (P < 0.001, r = 0.213), HER-2 (P = 0.008, r = 0.157), and Ki67 (P < 0.0002, r = 0.219). It was inversely linked to the estrogen receptor (P < 0.001, r = -0.291). Overexpression of YB-1 in a breast cancer cell line increased HER-2 and EGFR. Alternatively, mutation of YB-1 at Ser(102) > Ala(102) prevented the induction of these receptors and rendered the cells less responsive to EGF. The mutant YB-1 protein was also unable to optimally bind to the EGFR and HER-2 promoters based on chromatin immunoprecipitation. Furthermore, knocking down YB-1 with small interfering RNA suppressed the expression of EGFR and HER-2. This was coupled with a decrease in tumor cell growth. In conclusion, YB-1(Ser(102)) is a point of molecular vulnerability for maintaining the expression of EGFR and HER-2. Targeting YB-1 or more specifically YB-1(Ser(102)) are novel approaches to inhibiting the expression of these receptors to ultimately suppress tumor cell growth.

Breast Neoplasms↗

PubMed2006

MDM2 protein expression is a negative prognostic marker in breast carcinoma.

The protein encoded by the MDM2 oncogene inhibits the function of p53, leading to increased cell growth, avoidance of apoptosis, tolerance of genetic instability, and resistance to chemotherapy. The present study was performed to evaluate the relationship between MDM2 protein expression and survival in breast carcinoma. Two series of cases were used in this study: the first to identify the cutoff to be used in the interpretation of MDM2 immunostaining and perform preliminary survival analysis, and a second, independent series, to validate the findings from the first series and to perform multivariate analysis. For both series, archival sections of tissue microarrays were stained with anti-MDM2 antibody (NeoMarkers, Fremont, CA, USA) and MDM2 staining intensity was scored semiquantitatively. In the first series, 49 of 362 (14%) interpretable cases were positive for MDM2 expression, with 35 (10%) showing weak positivity and 14 (4%) strong positivity. Patients with MDM2-positive tumours had a significantly worse disease-specific survival than patients with MDM2-negative tumours (P=0.0022, 10-year DSS 61% (95% CI: 45-73) vs 73% (95% CI: 67-77)). No significant difference in survival was observed between patients with strongly and weakly MDM2-positive tumours (P=0.3). Accordingly, in the independent validation series weak and strong MDM2 positivity were combined and considered to be MDM2 positive. MDM2 expression was seen in 230/1747 (13%) interpretable cases in this series, with a significant difference (P<0.0001) in DSS between MDM2-negative and MDM2-positive cases (10 year DSS 58% (95% CI: 51-64) vs 73% (95% CI: 70-75)). MDM2 was an independent prognostic marker (HR=1.35, P=0.02) in a Cox regression model including MDM2 expression, tumour grade, nodal status, ER status and tumour size. Immunohistochemical studies of MDM2 in more than 2000 breast carcinomas show that MDM2 is an independent negative prognostic marker.

Biomarkers, Tumor↗

PubMed2005

NRG1 gene rearrangements in clinical breast cancer: identification of an adjacent novel amplicon associated with poor prognosis.

Rearrangements of the neuregulin (NRG1) gene have been implicated in breast carcinoma oncogenesis. To determine the frequency and clinical significance of NRG1 aberrations in clinical breast tumors, a breast cancer tissue microarray was screened for NRG1 aberrations by fluorescent in situ hybridization (FISH) using a two-color split-apart probe combination flanking the NRG1 gene. Rearrangements of NRG1 were identified in 17/382 cases by FISH, and bacterial artificial chromosome array comparative genomic hybridization was applied to five of these cases to further map the chromosome 8p abnormalities. In all five cases, there was a novel amplicon centromeric to NRG1 with a minimum common region of amplification encompassing two genes, SPFH2 and FLJ14299. Subsequent FISH analysis for the novel amplicon revealed that it was present in 63/262 cases. Abnormalities of NRG1 did not correlate with patient outcome, but the novel amplicon was associated with poor prognosis in univariate analysis, and in multivariate analysis was of prognostic significance independent of nodal status, tumor grade, estrogen receptor status, and human epidermal growth factor receptor (HER)2 overexpression. Of the two genes in the novel amplicon, expression of SPFH2 correlated most significantly with amplification. This amplicon may emerge as a result of breakpoints and chromosomal rearrangements within the NRG1 locus.

Breast Neoplasms↗

PubMed2005

Akt phosphorylates the Y-box binding protein 1 at Ser102 located in the cold shock domain and affects the anchorage-independent growth of breast cancer cells.

Akt/PKB is a serine/threonine kinase that promotes tumor cell growth by phosphorylating transcription factors and cell cycle proteins. There is particular interest in finding tumor-specific substrates for Akt to understand how this protein functions in cancer and to provide new avenues for therapeutic targeting. Our laboratory sought to identify novel Akt substrates that are expressed in breast cancer. In this study, we determined that activated Akt is positively correlated with the protein expression of the transcription/translation factor Y-box binding protein-1 (YB-1) in primary breast cancer by screening tumor tissue microarrays. We therefore questioned whether Akt and YB-1 might be functionally linked. Herein, we illustrate that activated Akt binds to and phosphorylates the YB-1 cold shock domain at Ser102. We then addressed the functional significance of disrupting Ser102 by mutating it to Ala102. Following the stable expression of Flag:YB-1 and Flag:YB-1 (Ala102) in MCF-7 cells, we observed that disruption of the Akt phosphorylation site on YB-1 suppressed tumor cell growth in soft agar and in monolayer. This correlated with an inhibition of nuclear translocation by the YB-1(Ala102) mutant. In conclusion, YB-1 is a new Akt substrate and disruption of this specific site inhibits tumor cell growth.

Breast Neoplasms↗

PubMed2005

Nuclear beta-catenin in mesenchymal tumors.

Beta-catenin is a crucial part of the Wnt and E-cadherin signalling pathways, which are involved in tumorigenesis. Dysregulation of these pathways allow beta-catenin to accumulate and translocate to the nucleus, where it may activate oncogenes. Such nuclear accumulation can be detected by immunohistochemistry, which may be useful in diagnosis. Although the role of beta-catenin has been established in various types of carcinomas, relatively little is known about its status in mesenchymal tumors. A number of studies suggest that beta-catenin dysregulation is important in desmoid-type fibromatosis, as well as in synovial sarcoma. We wished to determine whether nuclear beta-catenin expression is specific to and sensitive for particular bone and soft-tissue tumors, including sporadic desmoid-type fibromatosis. We studied the nuclear expression of beta-catenin using tissue microarrays in a comprehensive range of bone and soft-tissue tumor types. A total of 549 cases were included in our panel. Nuclear immunohistochemical staining was determined to be either high level (>25% of cells), low level (0-25%) or none. High-level nuclear beta-catenin staining was seen in a very limited subset of tumor types, including desmoid-type fibromatosis (71% of cases), solitary fibrous tumor (40%), endometrial stromal sarcoma (40%) and synovial sarcoma (28%). Although occasional cases of fibrosarcoma, clear cell sarcoma and carcinosarcoma had high-level staining, no high-level nuclear beta-catenin expression was seen in any of 381 fibrohistocytic, muscular, adipocytic, chondroid or osseous tumor cases representing 42 diagnostic categories. All primary immunostain tissue microarray images are made publicly accessible in a searchable database. High-level nuclear beta-catenin staining serves as a useful diagnostic tool, as it is specific to a small subset of mesenchymal tumors.

Cell Nucleus↗

PubMed2005

TMA-Combiner, a simple software tool to permit analysis of replicate cores on tissue microarrays.

We have previously published a suite of software tools that facilitates the reformulation of tissue microarray (TMA) data so that it may be analyzed using techniques originally devised for analysis of cDNA microarray data. However, current microarray data often feature multiple scores for a given tissue sample and antibody combination. Furthermore, an efficient and systematic method for combining scores that takes into account the differing staining properties of tissue epitopes has not been described. We thus present the TMA-Combiner, a new Microsoft Excel-based macro that permits analysis of data for which tissues may have two or more scores per antibody, and permits combination of data from multiple different tissue microarrays. It accomplishes this by rendering one score per tissue per antibody from two or more scores, using one of multiple user-selectable combination rules developed to account for the differing staining properties of tissue epitopes. This greatly facilitates analysis of tissue microarrays, particularly for users with large repositories of data, and may facilitate discovery of biological trends and help refine diagnostic accuracy of tissue markers in clinical samples.

Cluster Analysis↗

PubMed2005

Assessment of Her-1, Her-2, And Her-3 expression and Her-2 amplification in advanced stage ovarian carcinoma.

The human epidermal growth factor receptor (Her) family of receptor tyrosine kinases includes Her-1, Her-2, and Her-3. The overexpression of Her-1 and Her-2 have been reported previously in surface epithelial ovarian cancer. Although up to one-third of ovarian carcinomas have been found to have amplification or overexpression of Her-2, responses to trastuzumab therapy in these patients have been disappointing. In this study, we examined Her-1, Her-2, and Her- 3 protein expression as well as the frequency of Her-2 amplification in a series of 103 high-grade, advanced-stage (FIGO stage III or IV) ovarian surface epithelial carcinomas. Immunohistochemical staining using commercially available antibodies against Her-1-3 and fluorescence in situ hybridization (FISH) using probes against Her-2 and chromosome 17 centromere (CEP) were performed on a tissue microarray containing cores of tumor from 103 surface epithelial carcinomas (85 serous, 6 mixed surface epithelial, 5 clear cell, 3 endometrioid, 3 undifferentiated, 1 mucinous). Nine of 99 (9.1%) tumors were positive for Her-1 expression and 5 of 102 (4.9%) tumors were positive for Her-2 expression, with 1 showing strong immunoreactivity. None of the Her-1 positive tumors exhibited Her-2 immunoreactivity. There was no correlation between Her-1 or Her-2 expression and survival. Using Her-2:centromere fluorescence ratios of 2.0 or 1.5 as cutoffs in assessment of Her-2 amplification, 8 of 75 (10.7%) and 25 of 75 (33.3%) tumors, respectively, showed Her-2 amplification. Two of eight tumors that showed higher level (>2) Her-2 amplification by FISH also were positive for Her-2 by immunohistochemistry. Only 3 of 103 tumors expressed Her-3. Immunoreactivity for Her-1 and Her-2 was less frequently observed in this series than has been previously reported. The strong correlation between Her-2 immunostaining and amplification characteristic of breast carcinoma is not seen in ovarian carcinoma. These results indicated that few patients with ovarian carcinoma have tumors that would benefit from therapy targeted specifically against Her-1, Her-2, or Her-3.

Biomarkers, Tumor↗

PubMed2004

Hierarchical clustering analysis of tissue microarray immunostaining data identifies prognostically significant groups of breast carcinoma.

Prognostically relevant cluster groups, based on gene expression profiles, have been recently identified for breast cancers, lung cancers, and lymphoma. Our aim was to determine whether hierarchical clustering analysis of multiple immunomarkers (protein expression profiles) improves prognostication in patients with invasive breast cancer. A cohort of 438 sequential cases of invasive breast cancer with median follow-up of 15.4 years was selected for tissue microarray construction. A total of 31 biomarkers were tested by immunohistochemistry on these tissue arrays. The prognostic significance of individual markers was assessed by using Kaplan-Meier survival estimates and log-rank tests. Seventeen of 31 markers showed prognostic significance in univariate analysis (P < or = 0.05) and 4 markers showed a trend toward significance (P < or = 0.2). Unsupervised hierarchical clustering analysis was done by using these 21 immunomarkers, and this resulted in identification of three cluster groups with significant differences in clinical outcome. chi2 analysis showed that expression of 11 markers significantly correlated with membership in one of the three cluster groups. Unsupervised hierarchical clustering analysis with this set of 11 markers reproduced the same three prognostically significant cluster groups identified by using the larger set of markers. These cluster groups were of prognostic significance independent of lymph node metastasis, tumor size, and tumor grade in multivariate analysis (P=0.0001). The cluster groups were as powerful a prognostic indicator as lymph node status. This work demonstrates that hierarchical clustering of immunostaining data by using multiple markers can group breast cancers into classes with clinical relevance and is superior to the use of individual prognostic markers.

Adult↗