Gene Signature In Breast Cancer Research Articles

Changes in mammary histology and transcriptome profiles by low-dose exposure to environmental phenols at critical windows of development

Exposure to environmental chemicals has been linked to altered mammary development and cancer risk at high doses using animal models. Effects at low doses comparable to human exposure remain poorly understood, especially during critical developmental windows. We investigated the effects of two environmental phenols commonly used in personal care products – methyl paraben (MPB) and triclosan (TCS) – on the histology and transcriptome of normal mammary glands at low doses mimicking human exposure during critical windows of development. Sprague-Dawley rats were exposed during perinatal, prepubertal and pubertal windows, as well as from birth to lactation. Low-dose exposure to MPB and TCS induced measurable changes in both mammary histology (by Masson's Trichrome Stain) and transcriptome (by microarrays) in a window-specific fashion. Puberty represented a window of heightened sensitivity to MPB, with increased glandular tissue and changes of expression in 295 genes with significant enrichment in functions such as DNA replication and cell cycle regulation. Long-term exposure to TCS from birth to lactation was associated with increased adipose and reduced glandular and secretory tissue, with expression alterations in 993 genes enriched in pathways such as cholesterol synthesis and adipogenesis. Finally, enrichment analyses revealed that genes modified by MPB and TCS were over-represented in human breast cancer gene signatures, suggesting possible links with breast carcinogenesis. These findings highlight the issues of critical windows of susceptibility that may confer heightened sensitivity to environmental insults and implicate the potential health effects of these ubiquitous environmental chemicals in breast cancer.

Embryonic stem cell gene expression signatures in the canine mammary tumor: a bioinformatics approach.

Canine breast cancer was considered as an ideal model of comparative oncology for the human breast cancer, as there is significant overlap between biological and clinical characteristics of the human and canine breast cancer. We attempt to clarify expression profile of the embryonic stem cell (ES) gene signatures in canine breast cancer. Using microarray datasets (GSE22516 and GSE20718), expression of the three major ES gene signatures (modules or gene-sets), including Myc, ESC-like, and PRC modules, was primarily analyzed through Gene-Set Enrichment Analysis (GSEA) method in tumor and healthy datasets. For confirmation of the primary results, an additional 13 ES gene-sets which were categorized into four groups including ES expressed (ES exp1 and ES exp2), NOS targets (Nanog targets, Oct4 targets, Sox2 targets, NOS targets, and NOS TFs), Polycomb targets (Suz12 targets, Eed targets, H3K27 bound, and PRC2 targets), and Myc targets (Myc targets1, and Myc targets2) were tested in the tumor and healthy datasets. Our results revealed that there is a valuable overlap between canine and human breast cancer ES gene-sets expression profile, where Myc and ESC-like modules were up-regulated and PRC module was down-regulated in metastatic canine mammary gland tumors. Further analysis of the secondary gene-sets indicated overexpression of the ES expressed, NOS targets (Nanog targets, Oct4 targets, Sox2 targets, and NOS targets), and Myc targets and underexpression of the Polycomb targets in metastatic canine breast cancer.

Prognostic and predictive immune gene signatures in breast cancer.

Here, we focus on molecular biomarkers derived from transcriptomic studies to summarize the recent advances in our understanding of the mechanisms associated with differential prognosis and treatment outcome in breast cancer. Breast cancer is certainly immunogenic; yet it has been historically resistant to immunotherapy. In the past few years, refined immunotherapeutic manipulations have been shown to be effective in a significant proportion of cancer patients. For example, drugs targeting the PD-1 immune checkpoint have been proven to be an effective therapeutic approach in several solid tumors including melanoma and lung cancer. Very recently, the activity of such therapeutics has also been demonstrated in breast cancer patients. Pari passu with the development of novel immune modulators, the transcriptomic analysis of human tumors unveiled unexpected and paradoxical relationships between cancer cells and immune cells. This review examines our understanding of the molecular pathways associated with intratumoral immune response, which represents a critical step for the implementation of stratification strategies toward the development of personalized immunotherapy of breast cancer.

Development and verification of the PAM50-based Prosigna breast cancer gene signature assay

Development and verification of the PAM50-based Prosigna breast cancer gene signature assay

Development and verification of the PAM50-based Prosigna breast cancer gene signature assay.

BackgroundThe four intrinsic subtypes of breast cancer, defined by differential expression of 50 genes (PAM50), have been shown to be predictive of risk of recurrence and benefit of hormonal therapy and chemotherapy. Here we describe the development of Prosigna™, a PAM50-based subtype classifier and risk model on the NanoString nCounter Dx Analysis System intended for decentralized testing in clinical laboratories.Methods514 formalin-fixed, paraffin-embedded (FFPE) breast cancer patient samples were used to train prototypical centroids for each of the intrinsic subtypes of breast cancer on the NanoString platform. Hierarchical cluster analysis of gene expression data was used to identify the prototypical centroids defined in previous PAM50 algorithm training exercises. 304 FFPE patient samples from a well annotated clinical cohort in the absence of adjuvant systemic therapy were then used to train a subtype-based risk model (i.e. Prosigna ROR score). 232 samples from a tamoxifen-treated patient cohort were used to verify the prognostic accuracy of the algorithm prior to initiating clinical validation studies.ResultsThe gene expression profiles of each of the four Prosigna subtype centroids were consistent with those previously published using the PCR-based PAM50 method. Similar to previously published classifiers, tumor samples classified as Luminal A by Prosigna had the best prognosis compared to samples classified as one of the three higher-risk tumor subtypes. The Prosigna Risk of Recurrence (ROR) score model was verified to be significantly associated with prognosis as a continuous variable and to add significant information over both commonly available IHC markers and Adjuvant! Online.ConclusionsThe results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumor's intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay. Subsequent analytical and clinical validation studies confirm the clinical accuracy and technical precision of the Prosigna PAM50 assay in a decentralized setting.Electronic supplementary materialThe online version of this article (doi:10.1186/s12920-015-0129-6) contains supplementary material, which is available to authorized users.

Abstract 5282: A 3q amplification gene signature associated with triple negative breast cancer lung-specific metastasis

Abstract Triple negative breast cancers (TNBC), devoid of expression of the estrogen, progesterone and HER2 receptors, are among the most aggressive and deadly breast cancers, with high rates of tumor recurrence and metastatic spread. New prognostic markers are needed to identify patients who are at the highest risk for developing metastases, which might assist in tailoring treatment strategies. We previously identified 20 candidate driver genes in Chromosome 3q26-29, a critical amplified region in many human cancers including breast and lung cancer. The aim of this study was to assess the prognostic power of this 20-gene signature in TNBC patients. 855 breast tumors combined from four breast cancer cohorts (GSE12276, GSE2603, GSE2034 and NKI295) were used to evaluate the signature for prediction of organ-specific distant metastasis free survival (DMFS). The predictive ability of the 20-gene signature was evaluated by Cox proportional hazards model and was compared against other published breast cancer gene signatures including MammaPrint (70-gene), Veridex (76-gene), PAM50, 54 lung metastasis signature genes, HIF1 hypoxia pathway (8-gene), TGF β pathway (153-gene), BACH1 pathway metastasis gene signature (25-gene) and Gene Expression Prognostic Index Using Subtypes (GENIUS). The 20-gene signature was strongly associated with worse lung-specific metastasis-free survival (HR, 2.0, 95%CI, 1.4 to 2.87, P=0.00014) in TNBC patients (n = 131), independently of intrinsic subtype or published gene signatures and less so in non-TNBC patients (n = 724, HR, 1.3, 95%CI, 1.01 to 1.69, P=0.04). In conclusion, we discovered an amplified 20-gene signature in 3q26-29 that are associated with lung metastasis in patients with TNBC, suggesting on a potential role of 3q genes in the mechanism of lung-specific metastasis and incriminating cancer driver genes in this location as potential attractive novel therapeutic targets in this disease. The work is supported by the NIH Grant R01 CA102353 to PPM. Citation Format: Jun Qian, Heidi Chen, Pierre P. Massion. A 3q amplification gene signature associated with triple negative breast cancer lung-specific metastasis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5282. doi:10.1158/1538-7445.AM2015-5282

Prognostic stromal gene signatures in breast cancer.

IntroductionGlobal gene expression analysis of tumor samples has been a valuable tool to subgroup tumors and has the potential to be of prognostic and predictive value. However, tumors are heterogeneous, and homogenates will consist of several different cell types. This study was designed to obtain more refined expression data representing different compartments of the tumor.MethodsFormalin-fixed paraffin-embedded stroma-rich triple-negative breast cancer tumors were laser-microdissected, and RNA was extracted and processed to enable microarray hybridization. Genes enriched in stroma were identified and used to generate signatures by identifying correlating genes in publicly available data sets. The prognostic implications of the signature were analyzed.ResultsComparison of the expression pattern from stromal and cancer cell compartments from three tumors revealed a number of genes that were essentially specifically expressed in the respective compartments. The stroma-specific genes indicated contribution from fibroblasts, endothelial cells, and immune/inflammatory cells. The gene set was expanded by identifying correlating mRNAs using breast cancer mRNA expression data from The Cancer Genome Atlas. By iterative analyses, 16 gene signatures of highly correlating genes were characterized. Based on the gene composition, they seem to represent different cell types. In multivariate Cox proportional hazard models, two immune/inflammatory signatures had opposing hazard ratios for breast cancer recurrence also after adjusting for clinicopathological variables and molecular subgroup. The signature associated with poor prognosis consisted mainly of C1Q genes and the one associated with good prognosis contained HLA genes. This association with prognosis was seen for other cancers as well as in other breast cancer data sets.ConclusionsOur data indicate that the molecular composition of the immune response in a tumor may be a powerful predictor of cancer prognosis.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-015-0530-2) contains supplementary material, which is available to authorized users.

RNA helicase DP103 and TAK1: a new connection in cancer

Article on new markers of tumor metastasis. The authors found that expression of DP103 was significantly upregulated in the metastatic basal subtype of breast cancers in 3 independent cohorts. This elevated DP103 expression correlated with metastatic breast cancer gene signatures and was strongly associated with patient survival. This study provides the first evidence that the RNA helicase DEAD-box protein DP103 is an NF-kB target that could form part of a positive feedback loop contributing to DP103- mediated regulation of TAK1 kinase activity on the major NF-kB kinase IKK2, thus implicating DP103 in the maintenance of this oncogenic signaling arm in human cancer.

Abstract 3734: Development of a nanostring copy number assay for a customized 55 gene panel using challenging formalin-fixed paraffin-embedded (ffpe) tumor samples

Abstract Introduction: Gene amplification/deletion is a common tactic employed by tumor cells to proliferate uncontrollably. Multiple methods have been developed to determine gene copy numbers, such as FISH, qPCR, and, more recently, Next Generation Sequencing (NGS). However, these methods have limitations: FISH and NGS are very labor intensive; and FISH and qPCR can detect only a limited number of targets. Therefore, it is imperative to develop methods that are more user-friendly and have increased multiplexing capabilities to detect copy number variations (CNV). Using a novel digital barcode technology, NanoString Technologies (Seattle, WA) has developed the nCounter® technology to meet these needs. This new technology will be especially valuable after the recent FDA approval of the ProsignaTM assay, a breast cancer gene signature assay for subtype classification to help guide treatment decisions. In the BioPharma group at Genoptix, Inc., Carlsbad, CA, we have started to assess the nCounter technology for copy number determinations in a CLIA laboratory setting. Methods: A cancer gene CNV panel composed of 55 genes was custom designed and evaluated. The CNV results of a subset of genes generated from our gene panel using the nCounter technology were compared with the results generated from qPCR, digital droplet PCR (ddPCR), FISH, publications, and NGS. Furthermore, assay robustness was tested by using different amounts and quality of input FFPE DNA. An initial comparison on the CNVs obtained from genomic DNA digested by Alu1 enzyme or sonicated by Bioruptor® Pico (Diagenode Inc, Denville, NJ). Finally, the effects of different DNA isolation methods on copy number determinations were also evaluated. Results: Overall, the copy numbers generated using nCounter technology were concordant with results from the abovementioned methods as analyzed by comparing selected genes with known CNVs. A wide range of FFPE DNA input (200ng-4ug) could be tolerated by the assay. Based on a limited number of samples, DNA isolation methods, such as Qiagen, Promega Maxwell® CSC, or Roche Cobas®, have minimal effect on copy numbers. Conclusions: With the short hands-on time, relative high level of automation, and no amplification requirements, nCounter technology is able to generate CNVs in good agreement with other established CNV methods. This new 55 cancer gene CNV assay may be useful in clinical trials to assist in patient stratification and care. Citation Format: Tingdong Tang, Wenge Shi, Loretta Hipolito, Julie Mayer, Jelveh Lameh, Shabnam Tangri, Reinhold Pollner. Development of a nanostring copy number assay for a customized 55 gene panel using challenging formalin-fixed paraffin-embedded (ffpe) tumor samples. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3734. doi:10.1158/1538-7445.AM2014-3734

A program to identify prognostic and predictive gene signatures.

BackgroundThe advent of high-throughput technologies to profile human tumors has generated unprecedented insight into our molecular understanding of cancer. However, analysis of such high dimensional data is challenging and requires significant expertise which is not routinely available to many cancer researchers.ResultsTo overcome this limitation, we developed a freely accessible and user friendly Program to Identify Molecular Signatures (PIMS). Importantly, such signatures allow important insight into cancer biology, as well as provide clinical tools to identify potential biomarkers that might provide means to accurately stratify patients into different risk or treatment groups. We evaluated the performance of PIMS by identifying and testing predictive and prognostic gene signatures for breast cancer, using multiple breast tumor microarray cohorts representing hundreds of patients. Importantly, PIMS identified signatures classified patients into high and low risk groups with at least similar performance to other commonly used gene signature selection techniques.ConclusionsOur program is contained entirely within a Microsoft Excel file and therefore requires no installation of any additional programs or training. Hence, PIMS provides an accessible tool for cancer researchers to identify predictive and prognostic gene signatures to advance their research.Electronic supplementary materialThe online version of this article (doi:10.1186/1756-0500-7-546) contains supplementary material, which is available to authorized users.

Systematic assessment of prognostic gene signatures for breast cancer shows distinct influence of time and ER status

BackgroundThe aim was to assess and compare prognostic power of nine breast cancer gene signatures (Intrinsic, PAM50, 70-gene, 76-gene, Genomic-Grade-Index, 21-gene-Recurrence-Score, EndoPredict, Wound-Response and Hypoxia) in relation to ER status and follow-up time.MethodsA gene expression dataset from 947 breast tumors was used to evaluate the signatures for prediction of Distant Metastasis Free Survival (DMFS). A total of 912 patients had available DMFS status. The recently published METABRIC cohort was used as an additional validation set.ResultsSurvival predictions were fairly concordant across most signatures. Prognostic power declined with follow-up time. During the first 5 years of followup, all signatures except for Hypoxia were predictive for DMFS in ER-positive disease, and 76-gene, Hypoxia and Wound-Response were prognostic in ER-negative disease. After 5 years, the signatures had little prognostic power. Gene signatures provide significant prognostic information beyond tumor size, node status and histological grade.ConclusionsGenerally, these signatures performed better for ER-positive disease, indicating that risk within each ER stratum is driven by distinct underlying biology. Most of the signatures were strong risk predictors for DMFS during the first 5 years of follow-up. Combining gene signatures with histological grade or tumor size, could improve the prognostic power, perhaps also of long-term survival.

Prognostic Value of Gene Signatures and Proliferation in Lymph-Node-Negative Breast Cancer

IntroductionThe overall survival rate is good for lymph-node-negative breast cancer patients, but they still suffer from serious over- and some undertreatments. Prognostic and predictive gene signatures for node-negative breast cancer have a high number of genes related to proliferation. The prognostic value of gene sets from commercial gene-expression assays were compared with proliferation markers.MethodsIllumina WG6 mRNA microarray analysis was used to examine 94 fresh-frozen tumour samples from node-negative breast cancer patients. The patients were divided into low- and high-risk groups for distant metastasis based on the MammaPrint-related genes, and into low-, intermediate- and high-risk groups based on the recurrence score algorithm with genes included in Oncotype DX. These data were then compared to proliferation status, as measured by the mitotic activity index, the expressions of phosphohistone H3 (PPH3), and Ki67.ResultsKaplan-Meier survival analysis for distant-metastasis-free survival revealed that patients with weak and strong PPH3 expressions had 14-year survival rates of 87% (n = 45), and 65% (n = 49, p = 0.014), respectively. Analysis of the MammaPrint classification resulted in 14-year survival rates of 80% (n = 45) and 71% (n = 49, p = 0.287) for patients with low and high risks of recurrence, respectively. The Oncotype DX categorization yielded 14-year survival rates of 83% (n = 18), 79% (n = 42) and 68% (n = 34) for those in the low-, intermediate- and high-risk groups, respectively (p = 0.52). Supervised hierarchical cluster analysis for distant-metastasis-free survival in the subgroup of patients with strong PPH3 expression revealed that the genes involved in Notch signalling and cell adhesion were expressed at higher levels in those patients with distant metastasis.ConclusionThis pilot study indicates that proliferation has greater prognostic value than the expressions of either MammaPrint- or Oncotype-DX-related genes. Furthermore, in the subgroup of patients with high proliferation, Notch signalling pathway genes appear to be expressed at higher levels in patients who develop distant metastasis.

Breast tumor subgroups reveal diverse clinical prognostic power

Predicting the outcome of cancer therapies using molecular features and clinical observations is a key goal of cancer biology, which has been addressed comprehensively using whole patient datasets without considering the effect of tumor heterogeneity. We hypothesized that molecular features and clinical observations have different prognostic abilities for different cancer subtypes, and made a systematic study using both clinical observations and gene expression data. This analysis revealed that (1) gene expression profiles and clinical features show different prognostic power for the five breast cancer subtypes; (2) gene expression data of the normal-like subgroup contains more valuable prognostic information and survival associated contexts than the other subtypes, and the patient survival time of the normal-like subtype is more predictable based on the gene expression profiles; and (3) the prognostic power of many previously reported breast cancer gene signatures increased in the normal-like subtype and reduced in the other subtypes compared with that in the whole sample set.

Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia.

BackgroundIn mammalians, HIF is a master regulator of hypoxia gene expression through direct binding to DNA, while its role in microRNA expression regulation, critical in the hypoxia response, is not elucidated genome wide. Our aim is to investigate in depth the regulation of microRNA expression by hypoxia in the breast cancer cell line MCF-7, establish the relationship between microRNA expression and HIF binding sites, pri-miRNA transcription and microRNA processing gene expression.MethodsMCF-7 cells were incubated at 1% Oxygen for 16, 32 and 48 h. SiRNA against HIF-1α and HIF-2α were performed as previously published. MicroRNA and mRNA expression were assessed using microRNA microarrays, small RNA sequencing, gene expression microarrays and Real time PCR. The Kraken pipeline was applied for microRNA-seq analysis along with Bioconductor packages. Microarray data was analysed using Limma (Bioconductor), ChIP-seq data were analysed using Gene Set Enrichment Analysis and multiple testing correction applied in all analyses.ResultsHypoxia time course microRNA sequencing data analysis identified 41 microRNAs significantly up- and 28 down-regulated, including hsa-miR-4521, hsa-miR-145-3p and hsa-miR-222-5p reported in conjunction with hypoxia for the first time. Integration of HIF-1α and HIF-2α ChIP-seq data with expression data showed overall association between binding sites and microRNA up-regulation, with hsa-miR-210-3p and microRNAs of miR-27a/23a/24-2 and miR-30b/30d clusters as predominant examples. Moreover the expression of hsa-miR-27a-3p and hsa-miR-24-3p was found positively associated to a hypoxia gene signature in breast cancer. Gene expression analysis showed no full coordination between pri-miRNA and microRNA expression, pointing towards additional levels of regulation. Several transcripts involved in microRNA processing were found regulated by hypoxia, of which DICER (down-regulated) and AGO4 (up-regulated) were HIF dependent. DICER expression was found inversely correlated to hypoxia in breast cancer.ConclusionsIntegrated analysis of microRNA, mRNA and ChIP-seq data in a model cell line supports the hypothesis that microRNA expression under hypoxia is regulated at transcriptional and post-transcriptional level, with the presence of HIF binding sites at microRNA genomic loci associated with up-regulation. The identification of hypoxia and HIF regulated microRNAs relevant for breast cancer is important for our understanding of disease development and design of therapeutic interventions.

Gene expression markers in circulating tumor cells may predict bone metastasis and response to hormonal treatment in breast cancer

Circulating tumor cells (CTCs) have recently attracted attention due to their potential as prognostic and predictive markers for the clinical management of metastatic breast cancer patients. The isolation of CTCs from patients may enable the molecular characterization of these cells, which may help establish a minimally invasive assay for the prediction of metastasis and further optimization of treatment. Molecular markers of proven clinical value may therefore be useful in predicting disease aggressiveness and response to treatment. In our earlier study, we identified a gene signature in breast cancer that appears to be significantly associated with bone metastasis. Among the genes that constitute this signature, trefoil factor 1 (TFF1) was identified as the most differentially expressed gene associated with bone metastasis. In this study, we investigated 25 candidate gene markers in the CTCs of metastatic breast cancer patients with different metastatic sites. The panel of the 25 markers was investigated in 80 baseline samples (first blood draw of CTCs) and 30 follow-up samples. In addition, 40 healthy blood donors (HBDs) were analyzed as controls. The assay was performed using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) with RNA extracted from CTCs captured by the CellSearch system. Our study indicated that 12 of the genes were uniquely expressed in CTCs and 10 were highly expressed in the CTCs obtained from patients compared to those obtained from HBDs. Among these genes, the expression of keratin 19 was highly correlated with the CTC count. The TFF1 expression in CTCs was a strong predictor of bone metastasis and the patients with a high expression of estrogen receptor β in CTCs exhibited a better response to hormonal treatment. Molecular characterization of these genes in CTCs may provide a better understanding of the mechanism underlying tumor metastasis and identify gene markers in CTCs for predicting disease progression and response to treatment.

Gene Signatures in Breast Cancer: Current and Future Uses

Gene signatures have been developed for estrogen receptor-positive breast cancer to complement pathological factors in providing prognostic information. The 70-gene and the 21-gene signatures identify patients who may not require adjuvant chemotherapy. Gene signatures in triple-negative disease and HER2-positive disease have not been fully developed yet, although studies demonstrate heterogeneity within these subgroups. Further research is needed before genotyping will help in making clinical decisions in triple-negative and HER2-positive disease. Molecular subtyping of breast cancer led to define luminal, basal, and HER2-enriched subtypes, which have specific clinical behavior. This approach may lead to identify new subgroups requiring specific therapies. Standardization of techniques will be required to translate investigations to the clinic.

305 - Immunohistochemical Ki67 Labeling Index has a Similar Proliferation Predictive Power as Various First-Generation Gene Signatures in Breast Cancer

ABSTRACT Background Immunohistochemical assessment of Ki67 labeling index (IHC Ki67) has been described as a prognostic and predictive marker for breast cancer. On the other hand, several genetic prognostic markers have been described for breast cancer However, few clinical data sets provide information on correlations between genomic markers, mRNA Ki67, and IHC Ki67 in the same cohort of patients with survival data. The objective of this study is to examine the association between immunohistochemical Ki67 labeling index, Ki67 mRNA expression level, and first-generation gene signatures in a cohort of breast cancer patients. Patients and methods We assessed associations between IHC Ki67 and first-generation gene signatures in a panel of 40 tumor samples, using an oligonucleotide microarray. Gene expression analyses included Ki67 alone (MKi67), 21-gene signature, Mitosis Kinome score signature (MKS), and Genomic grade index (GGI). Correlation coefficients were calculated by Spearman's rank correlation test. To assess the relationship between IHC Ki67 and survival outcomes, survival curves were calculated by the Kaplan–Meier method and compared with the log-rank test according to IHC Ki67. Results Median age at diagnosis was 51 years. Treatments included adjuvant chemotherapy (32 patients) and endocrine therapy (21 patients). IHC Ki67, MKi67, and 3 genetic markers were highly correlated in all cases (Rho: 0.71–0.79). Estrogen receptor (ER)-positive cases exhibited strong correlations between IHC Ki67 and other signatures (Rho: 0.79–0.83). ER-negative cases displayed slightly lower correlations (Rho: 0.61–0.74). In ER-positive cases, the low IHC Ki67 group exhibited significantly longer relapse-free survival (RFS) than the high IHC Ki67 group (p = 0.007). This difference was confirmed by multivariate analysis. Conclusions Our data indicate that IHC Ki67 exhibits similar predictive power for proliferation in ER-positive cancers as genomic markers. Further study of IHC Ki67 is needed to define prognostic factors and predictive factors for chemotherapy using central laboratory assessment. Disclosure All authors have declared no conflicts of interest.

Immunohistochemical Ki67 labeling index has similar proliferation predictive power to various gene signatures in breast cancer

The objective of this study was to examine the association between the immunohistochemical Ki67 labeling index (IHC Ki67), Ki67 mRNA expression level, and first-generation gene signatures in a cohort of breast cancer patients. We assessed associations between IHC Ki67 and first-generation gene signatures in a panel of 39 tumor samples, using an oligonucleotide microarray. Gene expression analyses included Ki67 alone (MKi67), 21-gene signature, mitosis kinome score signature, and genomic grade index. Correlation coefficients were calculated by Spearman's rank correlation test. In all cases, IHC Ki67, MKi67, and three genetic markers were highly correlated (ρ, 0.71-0.97). Estrogen receptor (ER)-positive cases showed strong correlations between IHC Ki67 and other signatures (ρ, 0.79-0.83). The ER-negative cases showed slightly lower correlations (ρ, 0.58-0.73). In ER-positive cases, the low IHC Ki67 group showed significantly longer relapse-free survival than the high IHC Ki67 group (P = 0.007). This difference was confirmed by multivariate analysis. Our data indicate that IHC Ki67 shows similar predictive power for proliferation in ER-positive cancers as genomic markers. Further study of IHC Ki67 is needed to define prognostic factors and predictive factors for chemotherapy using central laboratory assessment.

Abstract 2460: Extracellular matrix protein expression is associated with chemotherapy resistance in breast cancer

Abstract Extracellular matrix protein expression is associated with chemotherapy resistance in breast cancer Purpose: Biomarkers to predict sensitivity and resistance to chemotherapy are still lacking. A recent study reported that stromal gene signatures in breast cancer may predict chemoresistance. We aim to determine the changes of 5 extracellular matrix (ECM) proteins in response to neoadjuvant chemotherapy in breast cancer. Experimental design: 100 female patients with locally advanced or metastatic breast cancer were treated with 6 cycles of pre-operative alternating sequential doxorubicin and docetaxel. Immunohistochemistry staining for thrombospondin 1 (THBS1), tenascin C (TNC), fibronectin (FN), smooth muscle actin-α (α-SMA) and secreted protein acidic and rich in cysteine (SPARC) was performed on pre- and post-treatment core biopsies, and correlated with estrogen receptor status, intrinsic chemotherapy response, pathological lymph node involvement and survival. Changes in THBS1 and TNC in relation to chemoresponse was additionally evaluated with mass spectrometry, and further validated with immunohistochemistry in an independent cohort of 31 breast cancer patients. Results: High baseline THBS1 and SPARC and high post-treatment α-SMA expression were associated with poor overall survival (p<0.05 for each marker). High expression of combined baseline ECM proteins was an independent predictor for poor progression-free survival (HR 2.22, 95% CI 1.06-4.64, p=0.034) and overall survival (HR 5.94, 95% CI 2.25-15.71, p<0.001). After 1-2 cycles of chemotherapy, increased expression of THBS1 and TNC compared to baseline was seen in intrinsically resistant tumors (p<0.05 for both), and in patients with pathological lymph node involvement (p<0.05 for both), but not in sensitive ones. Mass spectrometric analyses revealed >2 fold increase in THBS1 and TNC expression compared to baseline in tumors that were intrinsically resistant to doxorubicin relative to sensitive ones. The association between THBS1 and TNC immunohistochemistry changes and chemotherapy resistance was confirmed in the validation cohort. Conclusions: Up-regulation in ECM proteins after chemotherapy was associated with clinical and pathological response to doxorubicin- and docetaxel-based neoadjuvant chemotherapy in breast cancer. Assessment of these proteins may uncover strategies to overcome drug resistance. Key words: ECM proteins, neoadjuvant chemotherapy, breast cancer, drug resistance Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2460. doi:1538-7445.AM2012-2460

Treatment of HER2 positive breast cancer patients

Breast cancer (BC) is the most common cancer in women. It is known already for years that BC is a heterogeneous disease. This has now been confirmed by BC gene signature by which at least four types of BC subtypes can be distinguished. Approximately 15 % of patients with BC have a »HER2 like« tumor. A distinctive feature of this subtype is an overexpression of HER2 protein and/or amplification of the HER2 gene. HER2 protein is a transmembrane receptor protein, which promotes tumor growth, replication, invasion and dissemination. Consequently, when diagnosed, HER2 positive tumors are usually larger, less-differentiated, and are more often accompanied by metastatic involvement of the axillary lymph nodes, as compared to HER2 negative tumors. Women with HER2 positive tumors are therefore at higher risk of cancer recurrence and death. With the introduction of targeted anti- HER2 therapy, the prognosis of HER2 disease has significantly improved. There are currently two antiHER2 drugs registered for use in general oncology practice. Trastuzumab is a monoclonal antibody directed toward the extracellular domain of HER2 protein. It is used for the treatment of metastatic BC and in adjuvant setting. It is more effective when combined with chemotherapy compared to monotherapy. Combined with chemotherapy, it prolongs time to progression and overall survival of patients with metastatic BC. A year of adjuvant treatment with trastuzumab reduces the risk of recurrence and death from BC by 50 % and 30 %, respectively. Lapatinib is a small molecule that binds to the intracellular domain of HER2 receptor. The drug is registered for the treatment of metastatic HER2 positive BC after failure to trastuzuamb therapy. Combined with chemotherapy or hormonal therapy, lapatinib prolongs time to progression in patients with metastatic BC. Several other antiHER2 drugs are currently under evaluation in clinical trials.