Emerging biomarkers in breast cancer care

Clinical performance of an analytically validated assay in comparison to microarray technology to assess PITX2 DNA-methylation in breast cancer

Significant evidence has accumulated that DNA-methylation of the paired-like homeodomain transcription factor 2 (PITX2) gene can serve as a prognostic and predictive biomarker in breast cancer. PITX2 DNA-methylation data have been obtained so far from microarray and polymerase chain reaction (PCR)-based research tests. The availability of an analytically validated in vitro methylation-specific real-time PCR assay format (therascreen PITX2 RGQ PCR assay) intended for the determination of the percent methylation ratio (PMR) in the (PITX2) promoter 2 prompted us to investigate whether the clinical performance of these different assay systems generate comparable clinical outcome data. Mathematically converted microarray data of a previous breast cancer study (n = 204) into PMR values leads to a PITX2 cut-off value at PMR 14.73. Recalculation of the data to experimentally equivalent PMRs with the PCR PITX2 assay leads to a cut-off value at PMR 12 with the highest statistical significance. This cut-off predicts outcome of high-risk breast cancer patients to adjuvant anthracycline-based chemotherapy (n = 204; Hazard Ratio 2.48; p < 0.001) comparable to microarray generated results (n = 204; Hazard ratio 2.32; p < 0.0001). The therascreen PITX2 RGQ PCR assay is an analytically validated test with high reliability and robustness and predicts outcome of high-risk breast cancer patients to anthracycline-based chemotherapy.

Genomic analysis of the ecdysone steroid signal at metamorphosis onset using ecdysoneless and EcRnullDrosophila melanogaster mutants

Steroid hormone gene regulation is often depicted as a linear transduction of the signal, from molecule release to the gene level, by activation of a receptor protein after being bound by its steroid ligand. Such an action would require that the hormone be present and bound to the receptor in order to have target gene response. Here, we present data that presents a novel perspective of hormone gene regulation, where the hormone molecule and its receptor have exclusive target gene regulation function, in addition to the traditional direct target genes. Our study is the first genome-wide analysis of conditional mutants simultaneously modeling the steroid and steroid receptor gene expression regulation. We have integrated classical genetic mutant experiments with functional genomics techniques in the Drosophila melanogaster model organism, where we interrogate the 20-hydroxyecdysone signaling response at the onset of metamorphosis. Our novel catalog of ecdysone target genes illustrates the separable transcriptional responses among the hormone, the pre-hormone receptor and the post-hormone receptor. We successfully detected traditional ecdysone target genes as common targets and also identified novel sets of target genes which where exclusive to each mutant condition. Around 12 % of the genome responds to the ecdysone hormone signal at the onset of metamorphosis and over half of these are independent of the receptor. In addition, a significant portion of receptor regulated genes are differentially regulated by the receptor, depending on its ligand state. Gene ontology enrichment analyses confirm known ecdysone regulated biological functions and also validate implicated pathways that have been indirectly associated with ecdysone signaling.

Efficacy and pharmacogenomic biomarkers in breast cancer

In patients with breast cancer, a number of biomarkers, such as estrogen receptor, progesterone receptor and HER2, are part of routine work-up and used to guide endocrine, cytotoxic and HER2-targeted treatment. Interaction among these markers may also impact on treatment response and is being investigated. Multigene assays have reached varying levels of validation and clinical use as predictive biomarkers of cytotoxic therapy in specific clinical situations. A number of pharmacogenomic biomarkers based on germline polymorphisms have reached some degree of validation for predicting variation in treatment response and treatment-associated adverse effects. The challenge of validating biomarkers will be exacerbated as the cost of nucleic acid sequencing rapidly declines and more potential biomarkers emerge. New, carefully designed approaches will be needed to address this issue and realize the potential of biomarkers in breast cancer.

Gene expression analysis in biomarker research and early drug development using function tested reverse transcription quantitative real-time PCR assays

The identification of new biomarkers is essential in the implementation of personalized health care strategies that offer new therapeutic approaches with optimized and individualized treatment. In support of hypothesis generation and testing in the course of our biomarker research an online portal and respective function-tested reverse transcription quantitative real-time PCR assays (RT-qPCR) facilitated the selection of relevant biomarker genes. We have established workflows applicable for convenient high throughput gene expression analysis in biomarker research with cell lines (in vitro studies) and xenograft mouse models (in vivo studies) as well as formalin-fixed paraffin-embedded tissue (FFPET) sections from various human research and clinical tumor samples. Out of 92 putative biomarker candidate genes selected in silico, 35 were shown to exhibit differential expression in various tumor cell lines. These were further analysed by in vivo xenograft mouse models, which identified 13 candidate genes including potential response prediction biomarkers and a potential pharmacodynamic biomarker. Six of these candidate genes were selected for further evaluation in FFPET samples, where optimized RNA isolation, reverse transcription and qPCR assays provided reliable determination of relative expression levels as precondition for differential gene expression analysis of FFPET samples derived from projected clinical studies. Thus, we successfully applied function tested RT-qPCR assays in our biomarker research for hypothesis generation with in vitro and in vivo models as well as for hypothesis testing with human FFPET samples. Hence, appropriate function-tested RT-qPCR assays are available in biomarker research accompanying the different stages of drug development, starting from target identification up to early clinical development. The workflow presented here supports the identification and validation of new biomarkers and may lead to advances in efforts to achieve the goal of personalized health care.

Differential expression of breast cancer-associated genes between stage- and age-matched tumor specimens from African- and Caucasian-American Women diagnosed with breast cancer

Background

Recent studies suggest that the poorer breast cancer outcome observed in African-American women (AAW) may, in part, result from underlying molecular factors. The purpose of this study was to investigate gene expression differences between Caucasian-American women (CAW) and AAW that may contribute to this poorer prognosis.

Methods

The expression of 84 genes involved in breast carcinoma prognosis, response to therapy, estrogen signaling, and tumor aggressiveness was assessed in age- and stage-matched CAW and AAW paraffin-embedded breast cancer specimens. The Wilcoxon–Mann–Whitney Test was used to identify genes with a significant difference in expression between CAW and AAW. To determine if the differentially expressed genes could segregate between the CAW and AAW, we performed semi-supervised principal component analysis (SSPCA).

Results

Twenty genes were differentially expressed between AAW and CAW. SSPCA incorporating these 20 genes segregated AAW and CAW into two distinct groups. AAW were significantly (p < 0.05) more likely to display aberrations in G₁/S cell-cycle regulatory genes, decreased expression of cell-adhesion genes, and low to no expression of ESR1, PGR, ERBB2 and estrogen pathway targets.

Conclusions

The gene expression differences identified between AAW and CAW may contribute to more aggressive disease, resistance to therapy, enhanced metastatic potential and poor clinical outcome. These findings support the hypothesis that breast cancer specimens collected from AAW display distinct gene expression differences compared to similar tissues obtained from CAW. Additional population-based studies are necessary to determine if these gene expression variations contribute to the highly aggressive and treatment-resistant breast cancer phenotype frequently observed in AAW.

Clinical utility of level-of-evidence-1 disease forecast cancer biomarkers uPA and its inhibitor PAI-1

The prognostic and/or predictive value of the cancer biomarkers, urokinase-type plasminogen activator (uPA) and its inhibitor (plasminogen activator inhibitor [PAI]-1), determined by ELISA in tumor-tissue extracts, was demonstrated for several cancer types in numerous clinically relevant retrospective or prospective studies, including a multicenter breast cancer therapy trial (Chemo-N0). Consequently, for the first time ever for any cancer biomarker for breast cancer, uPA and PAI-1 have reached the highest level of evidence, level-of-evidence-1. At present, two other breast cancer therapy trials, NNBC-3 and Plan B, also incorporating uPA and PAI-1 as treatment-assignment tools are in effect. Furthermore, small synthetic molecules targeting uPA are currently in Phase II clinical trials in patients afflicted with advanced cancer of the ovary, breast or pancreas.

Prospective evaluation of prognostic factors uPA/PAI-1 in node-negative breast cancer: phase III NNBC3-Europe trial (AGO, GBG, EORTC-PBG) comparing 6×FEC versus 3×FEC/3×Docetaxel

BACKGROUND

Today, more than 70% of patients with primary node-negative breast cancer are cured by local therapy alone. Many patients receive overtreatment by adjuvant chemotherapy due to inadequate risk assessment. So far, few clinical trials have prospectively evaluated tumor biology based prognostic factors. Risk assessment by a biological algorithm including invasion factors urokinase-type plasminogen activator (uPA) and its inhibitor plasminogen activator inhibitor type 1 (PAI-1) will assess up to 35-55% of node-negative patients as low-risk and thus avoid chemotherapy. In contrast, a clinical-pathological algorithm will only classify 20-40% of patients as low-risk. High-risk node-negative patients should receive chemotherapy. Anthracycline-based regimens are accepted as a standard, the additional benefit of taxanes remains an open question.

METHODS/DESIGN

The international NNBC3 ("Node Negative Breast Cancer 3-Europe") trial compares biological risk assessment (UP) using invasion factors uPA/PAI-1 with a clinical-pathological algorithm (CP). In this trial, the type of risk assessment (CP or UP) was chosen upfront by each center for its patients. Fresh frozen tissue was obtained to determine uPA/PAI-1 using an enzyme-linked immunosorbent assay (ELISA). Patients assessed as high-risk were stratified by human epidermal growth factor receptor 2 (HER2) status and then randomised to receive anthracycline-containing chemotherapy 5-Fluorouracil (F)/Epirubicin (E)/Cyclophosphymide (C) or an anthracycline-taxane sequence (FE(100)C*6 versus FE(100)C*3 followed by Docetaxel(100)*3).

DISCUSSION

In this trial, 4,149 node-negative patients with operable breast cancer from 153 centers in Germany and France were included since 2002. Measurement of uPA/PAI-1 by ELISA was performed with standardised central quality assurance for 2,497 patients (60%) from 56 "UP"-centers. The NNBC 3-Europe trial showed that inclusion of patients into a clinical phase III trial is feasible based on biological testing of fresh frozen tumor material. In addition, 2,661 patients were classified as high-risk and thus received chemotherapy. As adjuvant chemotherapy, 1,334 high-risk patients received FE(100)C-Docetaxel(100), and 1,327 received French FE(100)C. No unexpected toxicities were observed. Chemotherapy efficacy and comparison of UP with CP will be evaluated after longer follow-up.

TRIAL REGISTRATION

clinical Trials.gov NCT01222052.