A multi-marker QPCR panel for the detection of circulating tumor cells predicts survival in breast cancer patients

Abstract #305

The detection of circulating tumor cells (CTCs) in the blood of cancer patients is a promising tool for risk stratification, treatment tailoring, and monitoring of the disease state. We previously developed a QPCR-based detection platform for the semi-quantitation of circulating tumor cells in the peripheral blood of breast cancer patients. This CTC assay combines gene expression data from 4 tumor marker genes into a single score using a quadratic discriminant analysis, and is optimized such that positivity indicates tumor cell presence, and negativity indicates tumor cell absence. An initial cohort of metastatic patients demonstrated that score positivity was correlated to a significantly shorter time to disease progression.
 The current study aimed to validate these results by using the CTC assay in an independent, retrospective patient series consisting of 111 non-metastatic stage I-III breast cancer patients (median followup 7.3 years), 16 metastatic breast cancer patients, and 28 healthy controls. Assay score positivity was observed in 14 out of 16 (88%) metastatic patients, 16 out of 111 (14%) non-metastatic stage I-III patients, and 0 out of 28 (0%) healthy female controls.
 In the early stage patient group, a positive CTC score was correlated to significantly poorer relapse-free survival (HR = 3.6, 95% CI = 1.7-7.9, p < 0.01) and overall survival (HR = 3.2, 95% CI = 1.6-6.1, p < 0.01). The assay was particularly powerful in patients with no lymph node metastases at time of diagnosis (relapse-free survival HR = 13.0, 95%CI = 3.0-55.7, p < 0.01, overall survival HR = 6.3, 95% CI = 1.9-21.1, p < 0.01). This platform compared very favorably to the traditional immunohistochemistry-based assay for disseminated tumor cell detection in bone marrow utilizing pan-anticytokeratin staining (AE1/AE3), which was not a significant predictor of survival in this patient group (HR = 1.3, 95% CI = 0.6-2.4, p = 0.49). In multivariate analyses, our CTC assay was a significant, independent predictor of overall survival.
 Work is currently ongoing to expand the study to include an additional 500-600 patients which should serve as a robust validation of the assay. This CTC detection platform represents an objective assay with both high specificity and prognostic power, and could be an effective clinical tool for outcome prediction in breast cancer patients.
 This work was supported by the Sixth Framework Program of the European Commission as part of the international DISMAL collaboration for research into disseminated epithelial malignancies.

Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 305.

Comparison of the Agilent, ROMA/NimbleGen and Illumina platforms for classification of copy number alterations in human breast tumors

BACKGROUND

Microarray Comparative Genomic Hybridization (array CGH) provides a means to examine DNA copy number aberrations. Various platforms, brands and underlying technologies are available, facing the user with many choices regarding platform sensitivity and number, localization, and density distribution of probes.

RESULTS

We evaluate three different platforms presenting different nature and arrangement of the probes: The Agilent Human Genome CGH Microarray 44 k, the ROMA/NimbleGen Representational Oligonucleotide Microarray 82 k, and the Illumina Human-1 Genotyping 109 k BeadChip, with Agilent being gene oriented, ROMA/NimbleGen being genome oriented, and Illumina being genotyping oriented. We investigated copy number changes in 20 human breast tumor samples representing different gene expression subclasses, using a suite of graphical and statistical methods designed to work across platforms. Despite substantial differences in the composition and spatial distribution of probes, the comparison revealed high overall concordance. Notably however, some short amplifications and deletions of potential biological importance were not detected by all platforms. Both correlation and cluster analysis indicate a somewhat higher similarity between ROMA/NimbleGen and Illumina than between Agilent and the other two platforms. The programs developed for the analysis are available from http://www.ifi.uio.no/bioinf/Projects/.

CONCLUSION

We conclude that platforms based on different technology principles reveal similar aberration patterns, although we observed some unique amplification or deletion peaks at various locations, only detected by one of the platforms. The correct platform choice for a particular study is dependent on whether the appointed research intention is gene, genome, or genotype oriented.

The Arabidopsis thaliana genome contains at least 29 active genes encoding SET domain proteins that can be assigned to four evolutionarily conserved classes

SET domains are conserved amino acid motifs present in chromosomal proteins that function in epigenetic control of gene expression. These proteins can be divided into four classes as typified by their Drosophila members E(Z), TRX, ASH1 and SU(VAR)3-9. Homologs of all four classes have been identified in yeast and mammals, but not in plants. A BLASTP screening of the Arabidopsis genome identified 37 genes: three E(z) homologs, five trx homologs, four ash1 homologs and 15 genes similar to Su(var)3-9. Seven genes were assigned as trx-related and three as ash1-related. Only four genes have been described previously. Our classification is based on the characteristics of the SET domains, cysteine-rich regions and additional conserved domains, including a novel YGD domain. RT-PCR analysis, cDNA cloning and matching ESTs show that at least 29 of the genes are active in diverse tissues. The high number of SET domain genes, possibly involved in epigenetic control of gene activity during plant development, can partly be explained by extensive genome duplication in Arabidopsis. Additionally, the lack of introns in the coding region of eight SU(VAR)3-9 class genes indicates evolution of new genes by retrotransposition. The identification of putative nuclear localization signals and AT-hooks in many of the proteins supports an anticipated nuclear localization, which was demonstrated for selected proteins.