bluuebunny/crossref_metadata_2025_split huggingface dataset:
ER-α36, a variant of ER-α, is the estrogen receptor that mediates mitogenic estrogen signaling in breast cancer cells.
Authors: Ding L , Zhang X , Wang Z 
Published: December 2010

Abstract
Abstract #18
The role of endogenous estrogens in breast cancer etiology has been well established. Dysregulated estrogen signaling increases the rate of cell proliferation and thus the risk of breast cancer. However, despite widespread agreement that estrogens are involved in breast cancer etiology, the molecular mechanisms of estrogen action, especially those by which estrogen signaling stimulates mammary tumorigenesis and breast cancer progression have not been well established.&#x2028; Recently, we have identified and cloned a 36-kDa novel isoform of estrogen receptor α (ER-α36) that is generated from a promoter located in the first intron of the original 66-kDa ER-α (ER-α66) gene. The ER-α36 differs from the ER-α66 by lacking both transcriptional activation domains (AF-1 and AF-2) but retains the DNA-binding, dimerization and most of the ligand-binding domains. ER-α36 is mainly expressed on the plasma membrane and mediates membrane-initiated estrogen signaling that activates the MAPK/ERK pathway and stimulates cell proliferation. ER-α36 inhibits the genomic estrogen signaling mediated by the AF1 and AF2 domains of ER-α66 and ligand-dependent and -independent transactivation activities of ER-β. We designed and constructed shRNA expression vectors to express shRNAs specific for ER-α36 or ER-α66. We found that ER-positive breast cancer cells MCF7 and T47D expressing ER-α36 shRNA that successfully knockdown about 90% ER-α36 expression failed to respond to estrogen stimulation. However, estrogen strongly stimulated cell growth in MCF7 and T47D cells with ER-α66 knockdown. We found that some estrogen responsive genes such as c-Myc, CyclinD1 and progesterone receptor (PR) were induced through the extra-nuclear estrogen signaling pathway while pS2 was induced by the nuclear pathway. Our results for the first time demonstrated that ER-α36, not the original ER-α36 is the estrogen receptor that actually mediates estrogen-stimulated cell proliferation in breast cancer cells.&#x2028; Among 800 cases of human breast cancer specimens examined, ER-α36 is expressed in most of the breast cancer specimens, and even in 40% of ER-negative breast cancer cases that lack expression of ER-α66. In addition, ER-α36 expressing patients responded poorly to anti-estrogen Tamoxifen treatment. In vitro study revealed that breast cancer cells that highly express ER-α36 exhibited estrogen hypersensitivity and Tamoxifen resistance, consistent with the clinical evidence that breast cancers expressing ER-α36 exhibit higher degree of malignancy and poorer survival rate.&#x2028; Taken together, our results demonstrated that ER-α36 is a novel player in mitogenic estrogen signaling that plays an important role in estrogen stimulated mammary carcinogenesis.
Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 18.
Accuracy of breast ultrasound BI-RADS classification and final pathological assessment of breast lesions submitted to core biopsy or fine needle aspiration of a breast diagnostic referral center in South Brazil.
Authors: Duarte Filho D , Zignani JM , Zignani PM , Teixeira RM , Biesdorf M , Viegas JP , Ribeiro R , Alexandretti M , Weber B , Tadvald M , Graudenz MS , Caleffi M 
Published: December 2010

Abstract
Abstract #2002
Background: Breast cancer (BC) is the leading cancer related mortality in women from 40-69 years old in Brazil. In the current year, about 49,400 women are expected to be diagnosed with BC, 4,880 of these in the state of Rio Grande do Sul. Until preventive strategies can be implemented, or better therapies developed, BC mortality reduction can only come from improvement in detection. Radiologists involved in breast imaging should ensure that they have the necessary skills to carry out core biopsy (CB) and/or fine-needle aspiration (FNA) under all forms of image guidance. This quality control is crucial in countries of limited resources, where the costs generated by benign breast biopsies affect the whole public health system. This paper aims to provide a quality parameter on best practice for diagnostic interventional breast procedures and standards.&#x2028; Methods: 1,071 consecutive women with breast imaging (BI) abnormalities referred to the BI Center of the Moinhos de Vento Hospital for ultrasound (Us) guided breast CB or FNA between Oct/2003 and Oct/2007 were eligible. All patients in the study population underwent clinical and radiological examination. CB was performed by Us-guided automated gun method. The pathology reports were performed by 2 independent pathologists. All breast findings were classified according to the Us BIRADS system and were correlated to pathology results. An Us BIRADS 4 or 5 was considered a positive test. Sensitivity (Sen), specificity (Spe), predictive positive value (PPV), predictive negative value (PNV) and accuracy (Acc) were calculated.&#x2028; Results: Patient medium age was 45.5y (13-92y). Correlation results are summarized on table 1. In this sample, 88.7% of BC were ductal invasive carcinoma, 4.6% lobular invasive carcinoma, 1.2% ductal carcinoma in situ, 1.2% undifferentiated neoplasia, and 4.3% were other types of neoplasia. Sen of 93.3% (CI 87.7%-96.5%), Spe of 95% (93.3%-96.2%), PPV of 75.2% (68.3%Â81.1%), PNV of 98.8% (97.8%-99.4%) and an Acc of 94.7% were observed. &#x2028; Discussion: Us BIRADS classification allows an adjusted standardization of radiologists images interpretation, reproducing the correlation between this and the pathology. Periodic performance audit is the most meaningful way to demonstrate the success or failure in detecting otherwise occult BC, the ultimate indicator of BI performance. Radiologists involved in BI in our center have the requirements to carry out CB and/or FNA under Us image guidance, once the observed results are in accordance with the ACR Practice Guideline, published in 2005.&#x2028; &#x2028;
Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2002.
Fine tuning of the Van Nuys prognostic index (VNPI) 2003 by using genomic grade index (GGI): a new tool for ductal carcinoma in situ (DCIS).
Authors: Altintas S , Toussaint J , Lambein K , Huizing M , Durbeque V , Larsimont D , Van Marck E , Vermorken J , Tjalma W , Sotiriou C 
Published: December 2010

Abstract
Abstract #2020
Introduction: DCIS is a heterogeneous malignant condition of the breast with no standard of care. The updated VNPI 2003 is a practical tool in treatment decision making. Recently, the introduction of GGI has been shown to be one of the most important prognostic indicators in invasive breast cancer. A GGI based on the expression of 4 genes using RT-PCR was developed and validated in invasive BC. The aim of this study was to assess its prognostic value in DCIS.&#x2028; Methods: Real Time Polymerase Chain Reaction-GGI (RT-PCR-GGI) was applied on a DCIS population. Patients were assigned into 3 subgroups according to VNPI [low risk (score 4-6), intermediate risk (score 7-9) and high risk (score 10-12)] based on nuclear grade ± necrosis, tumor size, margin width and age. The prognostic performance of GGI was assessed by replacing pathologically determined nuclear grade by GGI: VNPI-GGI. Disease free survival (DFS) was calculated by Kaplan-Meier survival plots with log-rank significance&#x2028; Results: A total of 90 patients with DCIS were analyzed. The number of recurrences per VNPI subgroup was 1/15 in subgroup 1, 5/53 in subgroup 2 and 6/22 in subgroup 3. Ten out of these 12 patients showed invasive recurrence. No statistical significance was reached (log rank 0.349; HR 3.69 [95% 0.620-21.923], p= 0.151). However, application of VNPI-GGI identified three distinct subgroups with statistically different DFS (HR = 8.887 [95% CI: 1.2–65.7], p= 0.03). Interestingly, when the VNPI-GGI was applied on the patients with low histological grade, 25% were redistributed to the high-risk group (p = 0.008). Of note, when PCR-GGI was applied to the recurrent cases (N= 12), the genomic grade status was preserved from DCIS to the recurrence disease in 83% of them.&#x2028; Conclusions: RT-PCR-GGI incorporated into the VNPI improved its prognostic value for DCIS. This method has the potential to provide a powerful tool in DCIS management. Further validation is planned in a prospective trial with a larger patient population.
Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2020.
UCSC cancer genomics browser.
Authors: Zhu J , Sanborn JZ , Wang T , Hsu F , Benz S , Szeto C , Esserman L , Haussler D 
Published: December 2010

Abstract
Abstract #2022
As experimental techniques for a comprehensive survey of the cancer landscape mature, there is a great demand in the cancer research field to develop advanced analysis and visualization tools for the characterization and integrative analysis of the large, complex genomic datasets arising from different technology platforms.&#x2028; The UCSC Cancer Genomics Browser is a suite of web-based tools designed to integrate, visualize and analyze genomic and clinical data. The secured-access browser, available at https://cancer.cse.ucsc.edu/, consists of three major components: hgHeatmap, hgFeatureSorter, and hgPathSorter. The main panel, hgHeatmap, displays a whole-genome-oriented view of genome-wide experimental measurements for individual and sets of samples/patients alongside their clinical information. hgFeatureSorter and hgPathSorter together enable investigators to order, filter, aggregate and display data interactively based on any given feature set ranging from clinical features to annotated biological pathways to user-edited collections of genes. Standard and advanced statistical tools are available to provide quantitative analysis of whole genomic data or any of its subsets. The UCSC Cancer Genomics Browser is an extension of the UCSC Genome Browser; thus it inherits and integrates the Genome Browser's existing rich set of human biology and genetics data to enhance the interpretability of cancer genomics data.&#x2028; We demonstrate the UCSC Cancer Genomics Browser by integrating several independent studies on breast cancer including the I-SPY chemotherapy clinical trial and other studies focused on chemotherapeutic response or long-term survival. The types of data that are visualized and analyzed by the browser include microarray measurements of gene expression, copy number variation and phosphoprotein expression, MRI imaging measurements, and clinical parameters.&#x2028; Collectively, these tools facilitate a synergistic interaction among clinicians, experimental biologists, and bioinformaticians. They enable cancer researchers to better explore the breadth and depth of the cancer genomics data resources, and to further characterize molecular pathways that influence cellular dynamics and stability in cancer. Ultimately, insights gained by applying these tools may advance our knowledge of human cancer biology and stimulate the discovery of new prognostic and diagnostic markers, as well as the development of therapeutic and prevention strategies.&#x2028; Funding sources: CALGB CA31964 and CA33601, ACRIN U01 CA079778 and CA080098, NCI SPORE CA58207, California Institute for Quantitative Biosciences, NHGRI.
Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2022.
Validation and comparison of nomograms and scores to predict non-sentinel lymph node status in breast cancer patients with metastatic sentinel lymph node: a prospective multicentric study.
Authors: Coutant C , Houvenaeghel G , Olivier C , Fondrinier E , Marchal F , Guillemin F , Seince N , Barranger E , Thomas V , Lambaudie E , Daraï E , Uzan S , Levêque J , Rouzier R 
Published: December 2010

Abstract
Abstract #203
Background&#x2028; Five tools have been developed to predict non-SN status in breast cancer patients with SN metastasis: two nomograms (the Memorial Sloan-Kettering Cancer Center nomogram (MSKCC nomogram) and the nomogram developed by Degnim) and three scoring systems (the Tenon score, the score from the M.D. Anderson Cancer Center (MDA score), and the score developed by Saidi). Our purpose was to assess the validity of these tools in a prospective multicentric study of 561 SN-positive patients.&#x2028; Methods&#x2028; For 561 SN-positive patients who underwent ALND, we tested the accuracy of the five mathematical models. We calculated the false-negative (FN) rates and the areas under the receiver operating characteristics curves (AUC) as a measure of discriminatory capacity. We also tested the accuracy of each model in the subgroup of 246 patients with micrometastasis or isolated tumor cells in the SN; and in the subgroup of 165 patients with histological tumor size measuring more than 2 cm. Results were compared to the optimal logistic regression model that could be developed on the 561 patient cohort.&#x2028; Results&#x2028; At least one non-SN was positive in 147 patients (26.2%). The Tenon score, MSKCC nomogram, MDA score, nomogram of Degnim and score of Saidi applied to all 561 patients achieved AUCs of 0.81, 0.78, 0.73, 0.73, and 0.65 respectively. The FN rate were 4.4% (12/273), 6.5% (13/201), 5.7% (8/140), 12.5% (2/16) and 15% (21/140) respectively. In the subgroup of patients with only SN micrometastases, the FN rates were 2.9% (6/209) and 3.5% (5/143) for the Tenon score and the MSKCC nomogram respectively. The AUCs were 0.81 and 0.72 respectively&#x2028; In the subgroup of patients with histological tumor size measuring more than 2 cm, the FN rates were 0% (0/10) and 28.6% (4/14) for the Tenon score and the MSKCC nomogram respectively. The AUCs were 0.69 and 0.66 respectively. For comparison, a logistic regression model developed on this multicentric cohort yielded AUCs of 0.83, 0.82, and 0.75 for the whole cohort, patients with micrometastasis or isolated tumor cells in the SN and in patients with tumor &gt; 2 cm, respectively.&#x2028; Conclusion&#x2028; In this multicenter study, the Tenon score outperformed other scoring system. It was also more discriminant than other scores in patients with micrometastasis or isolated tumor cells in the SN and in patients with tumor &gt; 2 cm.
Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 203.
Phosphoproteomic study of breast cancer: high-throughput SH2 screening.
Authors: Machida K , Claffey KP , Thompson CM , Shin D , Mayer BJ 
Published: December 2010

Abstract
Abstract #2031
Background: Protein tyrosine phosphorylation plays an important role in breast cancer cells. Tyrosine kinases such as Src and HER-2 have been shown to be overexpressed in invasive breast cancer tissues, and thus are used as prognostic markers and therapeutic targets. However, substrate proteins for tyrosine kinases in breast cancer tissues have not been extensively studied due to technical difficulties including low sensitivity and large sample requirement. Recently we established a high-throughput method using Src homology 2 (SH2) domain probes, termed SH2 profiling, to profile proteomes based on interaction between SH2 domains and tyrosine-phosphorylated proteins. In this study we aimed to optimize the assay for breast cancer tissues and evaluate SH2 profiling based classification. Material and Methods: Protein lysates from 10 breast cancer patient tissues as well as cancer cell lines were prepared and spotted in multiple duplicates on a nitrocellulose membrane. The blocked membrane was incubated with HRP-labeled GST-SH2 domain probes using a 96 well chamber apparatus. Bound probes were detected by chemiluminescence and signals were quantified using densitometry. Quantitative SH2 binding profiles of breast cancer samples were compared using a hierarchical clustering program. Results and discussion: 1. Although signal-to-noise ratio of breast cancer tissues was relatively low compared to cell lines, possibly due to non-cancerous material in clinical samples, specific signal was detectable using as little as 100 micrograms of sample protein for the entire assay. 2. Unsupervised clustering analysis based on SH2 binding patterns correctly separated HER-2 positive from HER-2 negative tumors, indicating the diagnostic potential of this method. Further validation studies with more samples are needed. 3. Although phosphoproteomics has not yet been adopted in the clinic because of issues related to sample requirements, reproducibility, and sensitivity, this pilot study strongly suggests that clinical applications of phosphoproteomics are feasible. This study is supported by the Breast Cancer Alliance.
Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2031.
Identification of robust, clinically relevant phenotypes of breast cancer from genome scale molecular profiling.
Authors: Eklund AC , Qiyuan L , Juul N , Richardson AL , Szallasi Z 
Published: December 2010

Abstract
Abstract #2036
Genome scale analysis by microarrays or array CGH holds the promise to identify novel subclasses of breast cancer or characterize functional modules of clinical relevance in a robust fashion. However, the success of these endeavors is highly dependent on several factors such as the general noise structure and noise level of high throughput measurements or the strength of association between biomarkers/gene modules and clinical outcome. We will address two issues deeply rooted in the high throughput nature of genome scale profiling, which are relevant for the accurate analysis of clinical microarray data sets: systematic bias in clinical microarray data and establishing strategies that allow extracting robust, convergent information/classification from genome scale molecular profiling of breast cancer.&#x2028; As will be demonstrated, clinical microarray data are burdened with a high level of systematic bias. We identified sources of technical bias affecting many genes in concert, thus causing spurious correlations in clinical data sets and false associations between genes and clinical variables. A method will be presented to correct for technical bias in clinical microarray data, which increased concordance with known biological relationships in multiple data sets.&#x2028; Gene expression profiling based classification of breast cancer and prognostic or clinical response associated gene expression signatures are usually derived from a single data set. However, any result extracted from a single data set will reflect to a large extent the technical (which genes are measured reliably on the microarray) and biological (such as cohort selection) bias of the given cohort. An alternative approach uses multiple, in this case 5 different, analogous clinical data sets and determines the robust, convergent information emerging from the cross data-set analysis. We will present such a method, which will reduce the impact of data set specific bias and outline robust functional modules in breast cancer, ultimately leading to the reevaluation of gene expression profiling based subtyping and diagnostic gene expression signatures in breast cancer.&#x2028; Finally, we will present evidence for the existence of at least two fundamentally different types of genome instability in breast cancer with direct implications for response to chemotherapy.
Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2036.
Concentrations of plasminogen activator inhibitor type1 (PAI-I) and urokinase-type plasminogen aktivator (uPA) in primary breast cancer (BC) tissue and corresponding axillary lymph node metastasis.
Authors: Artmann A , Celik K , Kiechle M , Rummeny EJ , Schmitt M , Harbeck N 
Published: December 2010

Abstract
Abstract #2046
Background: Components of the plasminogen activator system play a key role in tumor invasion and metastasis. Tumor tissue levels of urokinase-type plasminogen activator (uPA) and its inhibitor PAI-1 showed a strong prognostic impact in node-negative and node-positive primary BC. uPA/PAI-1 were the first novel prognostic factors in primary BC reaching the highest level of evidence for their clinical utility and they have recently been recommended by ASCO for clinical decision making.&#x2028; Material and Methods: For the first time, correlations between uPA and PAI-1 concentrations in 73 primary tumor tissues and corresponding axillary lymphnodes (ALN) in node-negative (pN0) and node-positive (pN+) BC (1991-98) and their prognostic impact on disease-free (DFS) and overall survival (OS) were evaluated.&#x2028; Results: Median follow-up was 56 months. Overall, PAI-I (p=0,014) and uPA concentrations (p&lt;0,001) were significantly higher in tumour tissue than in the corresponding ALN. There was no significant difference of PAI-1 in primary tumor tissue between pN0 and pN+ disease. In involved ALN (pN+), concentrations of PAI-1 but not of uPA, were significantly higher than in pN0 (p&lt;0.001). Moreover, patients with higher PAI-1 concentrations in the corresponding ALN than in their primary tumor had a significantly shorter DFS (p&lt;0,001) and OS (p=0.005).&#x2028; Discussion: Our clinical findings support the basic research data implicating uPA and PAI-1 as key proteolytic factors in metastasis-asociated processes such as adhesion, angiogenesis, invasion, proliferation and migration. For the first time, we are able to demonstrate that particularly PAI-1 seems to be involved in tumor metastasis in primary breast cancer with its concentrations being higher in involved ALN than in the primary tumor. Besides uPA/PAI-1 being validated and clinically useful prognostic factors, interference with the uPA/PAI-1 system thus promises to be an interesting therapeutic concept in BC.
Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2046.