Bjørn Naume

Allele-specific copy number analysis of tumors

We present an allele-specific copy number analysis of the in vivo breast cancer genome. We describe a unique bioinformatics approach, ASCAT (allele-specific copy number analysis of tumors), to accurately dissect the allele-specific copy number of solid tumors, simultaneously estimating and adjusting for both tumor ploidy and nonaberrant cell admixture. This allows calculation of “ASCAT profiles” (genome-wide allele-specific copy-number profiles) from which gains, losses, copy number-neutral events, and loss of heterozygosity (LOH) can accurately be determined. In an early-stage breast carcinoma series, we observe aneuploidy (>2.7n) in 45% of the cases and an average nonaberrant cell admixture of 49%. By aggregation of ASCAT profiles across our series, we obtain genomic frequency distributions of gains and losses, as well as genome-wide views of LOH and copy number-neutral events in breast cancer. In addition, the ASCAT profiles reveal differences in aberrant tumor cell fraction, ploidy, gains, losses, LOH, and copy number-neutral events between the five previously identified molecular breast cancer subtypes. Basal-like breast carcinomas have a significantly higher frequency of LOH compared with other subtypes, and their ASCAT profiles show large-scale loss of genomic material during tumor development, followed by a whole-genome duplication, resulting in near-triploid genomes. Finally, from the ASCAT profiles, we construct a genome-wide map of allelic skewness in breast cancer, indicating loci where one allele is preferentially lost, whereas the other allele is preferentially gained. We hypothesize that these alternative alleles have a different influence on breast carcinoma development.

Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: gene expression analyses across three different platforms

BackgroundGene expression profiling has been used to define molecular phenotypes of complex diseases such as breast cancer. The luminal A and basal-like subtypes have been repeatedly identified and validated as the two main subtypes out of a total of five molecular subtypes of breast cancer. These two are associated with distinctly different gene expression patterns and more importantly, a significant difference in clinical outcome. To further validate and more thoroughly characterize these two subtypes at the molecular level in tumors at an early stage, we report a gene expression profiling study using three different DNA microarray platforms.ResultsExpression data from 20 tumor biopsies of early stage breast carcinomas were generated on three different DNA microarray platforms; Applied Biosystems Human Genome Survey Microarrays, Stanford cDNA Microarrays and Agilents Whole Human Genome Oligo Microarrays, and the resulting gene expression patterns were analyzed. Both unsupervised and supervised analyses identified the different clinically relevant subtypes of breast tumours, and the results were consistent across all three platforms. Gene classification and biological pathway analyses of the genes differentially expressed between the two main subtypes revealed different molecular mechanisms descriptive of the two expression-based subtypes: Signature genes of the luminal A subtype were over-represented by genes involved in fatty acid metabolism and steroid hormone-mediated signaling pathways, in particular estrogen receptor signaling, while signature genes of the basal-like subtype were over-represented by genes involved in cell proliferation and differentiation, p21-mediated pathway, and G1-S checkpoint of cell cycle-signaling pathways. A minimal set of 54 genes that best discriminated the two subtypes was identified using the combined data sets generated from the three different array platforms. These predictor genes were further verified by TaqMan® Gene Expression assays.ConclusionWe have identified and validated the two main previously defined clinically relevant subtypes, luminal A and basal-like, in a small set of early stage breast carcinomas. Signature genes characterizing these two subtypes revealed that distinct molecular mechanisms might have been pre-programmed at an early stage in different subtypes of the disease. Our results provide further evidence that these breast tumor subtypes represent biologically distinct disease entities and may require different therapeutic strategies. Finally, validated by multiple gene expression platforms, including quantitative PCR, the set of 54 predictor genes identified in this study may define potential prognostic molecular markers for breast cancer.

Detection of Isolated Tumor Cells in Bone Marrow Is an Independent Prognostic Factor in Breast Cancer

PURPOSE This study was performed to disclose the clinical impact of isolated tumor cell (ITC) detection in bone marrow (BM) in breast cancer. PATIENTS AND METHODS BM aspirates were collected from 817 patients at primary surgery. Tumor cells in BM were detected by immunocytochemistry using anticytokeratin antibodies (AE1/AE3). Analyses of the primary tumor included histologic grading, vascular invasion, and immunohistochemical detection of c-erbB-2, cathepsin D, p53, and estrogen receptor (ER)/progesterone receptor (PgR) expression. These analyses were compared with clinical outcome. The median follow-up was 49 months. RESULTS ITC were detected in 13.2% of the patients. The detection rate rose with increasing tumor size (P =.011) and lymph node involvement (P <.001). Systemic relapse and death from breast cancer occurred in 31.7% and 26.9% of the BM-positive patients versus 13.7% and 10.9% of BM-negative patients, respectively (P <.001). Analyzing node-positive and node-negative patients separately, ITC positivity was associated with poor prognosis in the node-positive group and in node-negative patients not receiving adjuvant therapy (T1N0). In multivariate analysis, ITC in BM was an independent prognostic factor together with node, tumor, and ER/PgR status, histologic grade, and vascular invasion. In separate analysis of the T1N0 patients, histologic grade was independently associated with both distant disease-free survival (DDFS) and breast cancer-specific survival (BCSS), ITC detection was associated with BCSS, and vascular invasion was associated with DDFS. CONCLUSION ITC in BM is an independent predictor of DDFS and BCSS. An unfavorable prognosis was observed for node-positive patients and for node-negative patients not receiving systemic therapy. A combination of several independent prognostic factors can classify subgroups of patients into excellent and high-risk prognosis groups.

Extracellular matrix signature identifies breast cancer subgroups with different clinical outcome

Prediction of the clinical outcome of breast cancer is multi‐faceted and challenging. There is growing evidence that the complexity of the tumour micro‐environment, consisting of several cell types and a complex mixture of proteins, plays an important role in development, progression, and response to therapy. In the current study, we investigated whether invasive breast tumours can be classified on the basis of the expression of extracellular matrix (ECM) components and whether such classification is representative of different clinical outcomes. We first examined the matrix composition of 28 primary breast carcinomas by morphology and gene expression profiling using 22K oligonucleotide Agilent microarrays. Hierarchical clustering of the gene expression profile of 278 ECM‐related genes derived from the literature divided the tumours into four main groups (ECM1–4). A set of selected differentially expressed genes was validated by immunohistochemistry. The robustness of the ECM classification was confirmed by studying the four ECM groups in a previously published gene expression data set of 114 early‐stage primary breast carcinomas profiled using cDNA arrays. Univariate survival analysis showed significant differences in clinical outcome among the various ECM subclasses. One set of tumours, designated ECM4, had a favourable outcome and was defined by the overexpression of a set of protease inhibitors belonging to the serpin family, while tumours with an ECM1 signature had a poorer prognosis and showed high expression of integrins and metallopeptidases, and low expression of several laminin chains. Furthermore, we identified three surrogate markers of ECM1 tumours: MARCO, PUNC, and SPARC, whose expression levels were associated with breast cancer survival and risk of recurrence. Our findings suggest that primary breast tumours can be classified based upon ECM composition and that this classification provides relevant information on the biology of breast carcinomas, further supporting the hypothesis that clinical outcome is strongly related to stromal characteristics. Copyright

miRNA-mRNA Integrated Analysis Reveals Roles for miRNAs in Primary Breast Tumors

Introduction Few studies have performed expression profiling of both miRNA and mRNA from the same primary breast carcinomas. In this study we present and analyze data derived from expression profiling of 799 miRNAs in 101 primary human breast tumors, along with genome-wide mRNA profiles and extensive clinical information. Methods We investigate the relationship between these molecular components, in terms of their correlation with each other and with clinical characteristics. We use a systems biology approach to examine the correlative relationship between miRNA and mRNAs using statistical enrichment methods. Results We identify statistical significant differential expression of miRNAs between molecular intrinsic subtypes, and between samples with different levels of proliferation. Specifically, we point to miRNAs significantly associated with TP53 and ER status. We also show that several cellular processes, such as proliferation, cell adhesion and immune response, are strongly associated with certain miRNAs. We validate the role of miRNAs in regulating proliferation using high-throughput lysate-microarrays on cell lines and point to potential drivers of this process. Conclusion This study provides a comprehensive dataset as well as methods and system-level results that jointly form a basis for further work on understanding the role of miRNA in primary breast cancer.

A concept for the standardized detection of disseminated tumor cells in bone marrow from patients with primary breast cancer and its clinical implementation

Numerous single‐institutional studies and a large pooled analysis have demonstrated that the presence of disseminated tumor cells (DTCs) in the bone marrow (BM) from patients with primary, nonmetastatic breast cancer (Stages I‐III) is associated with impaired prognosis. To date, sampling of BM and assessment of DTCs is not considered a routine procedure in the clinical management of breast cancer patients; however, emerging data suggest a future role for risk stratification and monitoring of therapeutic efficacy. Because these clinical options need to be evaluated in trials to verify the principle of this concept in the clinical setting, agreement on the standardized detection of DTCs is necessary. Consequently, the German, Austrian, and Swiss Societies for Senology recently formed a panel 1) to review and discuss the existing methodologies, 2) to find a consensus for a standardized detection of DTCs, and 3) to explore the options for its clinical implementation. Cancer 2006.

Isolated tumor cells in bone marrow three years after diagnosis in disease-free breast cancer patients predict unfavorable clinical outcome

Purpose: The aim of the study was to explore the value of analyzing bone marrow (BM) for the presence of isolated tumor cell(s) (ITCs) in disease-free breast cancer patients 3 years after diagnosis. Experimental Design: ITCs in BM at operation was found to be an independent prognostic factor in 817 breast cancer patients. Among these, 356 disease-free patients were analyzed with a second BM after 3 years follow-up (median 40 months, SD 3 months, range 29–52). ITC was detected by immunocytochemistry with anticytokeratine antibodies (AE1/AE3). Results: The population consisted of 70% T1 and 72% node-negative patients. ITC in BM was detected in 15%. At a median of 25 months since the second BM aspiration (66 months since diagnosis), 32 patients had developed relapse, 12 local and 20 systemic. Of the patients with ITC in BM, 21% relapsed compared with 7% of the ITC-negative patients (P < 0.001). Ten patients died of breast cancer. Survival analyses showed that ITC in BM predicted reduced distant disease-free survival (DDFS) and breast cancer specific survival (BCSS; P < 0.001, log-rank test). Uni-and multivariate analyses of the prognostic value of N, T, estrogen receptor/progesterone receptor, and BM status, histological grade, vascular invasion, p53-, c-erb-B2-, and cathepsin D expression were performed. BM status was the only independent prognostic factor for both DDFS and BCSS, whereas c-erbB-2 and N status were independent for BCSS and vascular invasion and T status for DDFS. Conclusions: ITC in BM 3 years after diagnosis in disease-free breast cancer patients is an independent prognostic factor. Detection of residual disease by BM analysis at follow-up may unravel insufficient adjuvant treatment. The clinical implications should be further explored.

Persistence of Disseminated Tumor Cells in the Bone Marrow of Breast Cancer Patients Predicts Increased Risk for Relapse—A European Pooled Analysis

Background: The prognostic significance of disseminated tumor cells (DTC) in bone marrow (BM) of breast cancer patients at the time of primary diagnosis has been confirmed by a large pooled analysis. In view of the lack of early indicators for secondary adjuvant treatment, we here evaluated whether the persistence of DTCs after adjuvant therapy increases the risk of subsequent relapse and death. Patients and Methods: Individual patient data from 676 women with primary diagnosis of early breast cancer stages I–III from 3 follow-up studies were pooled. During clinical follow-up, patients underwent BM aspiration (BMA) to determine the presence of DTC. Tumor cells were detected by the standardized immunoassays. Univariate and multivariable proportional hazards models were estimated to assess the prognostic significance of DTC for disease-free survival (DFS) and overall survival (OS). Results: Patients were followed for a median of 89 months. BMA was performed at median 37 months after diagnosis of breast cancer. At follow-up BMA, 15.5% of patients had DTCs. The presence of DTC was an independent indicator of poor prognosis for DFS, distant DFS (DDFS), cancer-specific survival, and OS during the first 5 years following cancer diagnosis (log-rank test P < 0.001 values for all investigated endpoints). Conclusion: Among breast cancer patients, persistent DTCs during follow-up significantly predicted the increased risk for subsequent relapse and death. Analysis of DTC might serve as a clinically useful monitoring tool and should be tested as an indicator for secondary adjuvant treatment intervention within clinical trials. Clin Cancer Res; 17(9); 2967–76. ©2011 AACR.

Immunocytochemical detection of isolated epithelial cells in bone marrow: non‐specific staining and contribution by plasma cells directly reactive to alkaline phosphatase

Detection of isolated tumour cells (TCs) in bone marrow (BM) from epithelial cancer patients by immunocytochemical (ICC) analysis seems to predict future relapse, but the reported percentages of positive BMs among patients with localized cancer show large variations and the number of detected TCs is low. This emphasizes the importance of thoroughly testing the methods in use. This study was performed to clarify to what extent positive staining of haematopoietic cells (HCs) interferes with the ICC detection of epithelial cells in BM. BM mononuclear cells (MNCs) from normal donors and stage I–II breast cancer patients were stained with anti‐cytokeratin (CK) and isotype control monoclonal antibodies (MAbs) followed by alkaline phosphatase (AP)‐based visualization of immunolabelled cells. In the ICC staining of normal donors by the anti‐CK MAbs AE1/AE3 or A45‐B/B3, rare immunoreactive cells were detected in 7/20 and 8/19 BMs, respectively. Morphological examination recognized all these cells as typical HCs. In the breast cancer patients (n=257), anti‐CK‐positive cells were detected in 26·6 per cent, excluding cells with HC morphology. Using the same morphological criteria, isotype control‐positive cells were detected in 5·4 per cent of patients. Some of the false‐positive events were further analysed and cells with strong reactivity against the AP enzyme alone were detected. Double ICC staining recognized the majority of these AP directly‐reactive cells as CD45‐negative and human Ig kappa/lambda‐positive, in accordance with the phenotype of mature plasma cells. Morphological evaluation and adequate controls are important to ensure the diagnostic specificity of micrometastases in BM. It is recommended that the number of BM MNCs included in negative controls should equal the number of cells in the diagnostic specimens.

Comparison of the clinical significance of occult tumor cells in blood and bone marrow in breast cancer

Immunocytochemical (ICC) detection of disseminated tumor cells (DTC) in bone marrow (BM) in early breast cancer is an independent prognostic factor. The significance of circulating tumor cells (CTC) in peripheral blood (PB) needs further exploration and comparison to DTC detection. PB and BM were prospectively collected from 341 breast cancer patients median 40 months after operation. PB samples were analyzed for tumor cells by a negative immunomagnetic technique (10 × 106 cells/test). BM aspirates were analyzed by standard ICC (2 × 106 cells/test). CTC were present in 10% of the patients and DTC in 14%. Thirty‐seven relapses and 14 breast cancer deaths have occurred at median 66 months after diagnosis. Both CTC‐status and DTC‐status were significantly associated with disease free survival (DFS) (event rate: CTC‐positive 26.5% vs. CTC‐negative 9.1%; DTC‐positive 29.2% vs. DTC‐negative 7.8%) (p < 0.001/p < 0.001, log rank) and breast cancer specific survival (event rate: CTC‐positive 17.6% vs. CTC‐negative 2.6%; DTC‐positive 12.5% vs. DTC‐negative 2.7%) (p < 0.001/p < 0.001). The presence of both CTC and DTC (n = 8) resulted in an especially poor prognosis (p < 0.001). In node negative patients, DTC‐status, but not CTC‐status, predicted differences in DFS (p = 0.006 vs. p = 0.503). Excluding 23 patients with breast cancer‐related events prior to the sample collections, CTC detection was not significantly associated with DFS/distant‐DFS (p = 0.158/0.193), in contrast to DTC detection (p < 0.001/<0.001). Presence of CTC and absence of DTC did not affect DFS (p = 0.516). Applied to early stage disease, CTC analysis of increased volumes of PB appears less sensitive and prognostic than standard DTC analysis. Currently, this does not support an exchange of BM with PB for analysis of occult tumor cells.