Pathway analysis of gene signatures predicting metastasis of node-negative primary breast cancer.

BACKGROUND: Published prognostic gene signatures in breast cancer have few genes in common. Here we provide a rationale for this observation by studying the prognostic power and the underlying biological pathways of different gene signatures. METHODS: Gene signatures to predict the development of metastases in estrogen receptor-positive and estrogen receptor-negative tumors were identified using 500 re-sampled training sets and mapping to Gene Ontology Biological Process to identify over-represented pathways. The Global Test program confirmed that gene expression profilings in the common pathways were associated with the metastasis of the patients. RESULTS: The apoptotic pathway and cell division, or cell growth regulation and G-protein coupled receptor signal transduction, were most significantly associated with the metastatic capability of estrogen receptor-positive or estrogen-negative tumors, respectively. A gene signature derived of the common pathways predicted metastasis in an independent cohort. Mapping of the pathways represented by different published prognostic signatures showed that they share 53% of the identified pathways. CONCLUSION: We show that divergent gene sets classifying patients for the same clinical endpoint represent similar biological processes and that pathway-derived signatures can be used to predict prognosis. Furthermore, our study reveals that the underlying biology related to aggressiveness of estrogen receptor subgroups of breast cancer is quite different.

Novel genes associated with malignant melanoma but not benign melanocytic lesions.

PURPOSE: Cutaneous melanoma is a common, aggressive cancer with increasing incidence. The identification of melanoma-specific deregulated genes could provide molecular markers for lymph node staging assays and further insight into melanoma tumorigenesis. EXPERIMENTAL DESIGN: Total RNA isolated from 45 primary melanoma, 18 benign skin nevi, and 7 normal skin tissue specimens were analyzed on an Affymetrix Hu133A microarray containing 22,000 probe sets. RESULTS: Hierarchical clustering revealed a distinct separation of the melanoma samples from the benign and normal specimens. Novel genes associated with malignant melanoma were identified. Differential gene expression of two melanoma-specific genes, PLAB and L1CAM, were tested by a one-step quantitative reverse transcription-PCR assay on primary malignant melanoma, benign nevi, and normal skin samples, as well as on malignant melanoma lymph node metastasis and melanoma-free lymph nodes. The performance of the markers was compared with conventional melanoma markers such as tyrosinase, gp100, and MART1. CONCLUSION: Our study systematically identified novel melanoma-specific genes and showed the feasibility of using a combination of PLAB and L1CAM in a reverse transcription-PCR assay to differentiate clinically relevant samples containing benign or malignant melanocytes.

Constitutive expression of proinflammatory complement components by subsets of neurons in the central nervous system.

The brain is largely protected from damage due to infection, trauma, and aberrant processes by the innate immune system. These studies were undertaken to determine whether neurons in normal brains constitutively express complement components. In situ hybridization and immunohistochemical studies with specific riboprobes and antibodies, respectively, revealed that most hippocampal neurons, many pyramidal cortical neurons and cerebellar Purkinje neurons in normal murine brains constitutively express C3, C5 and C6. The constitutive expression by neuronal subsets of components of the complement activation and membrane attack pathways suggests that the complement system represents a "first line" of host defense in the brain.

mRNA and microRNA expression profiles in circulating tumor cells and primary tumors of metastatic breast cancer patients.

PURPOSE: Molecular characterization of circulating tumor cells (CTC) holds great promise. Unfortunately, routinely isolated CTC fractions currently still contain contaminating leukocytes, which makes CTC-specific molecular characterization extremely challenging. In this study, we determined mRNA and microRNA (miRNA) expression of potentially CTC-specific genes that are considered to be clinically relevant in breast cancer. EXPERIMENTAL DESIGN: CTCs were isolated with the epithelial cell adhesion molecule-based CellSearch Profile Kit. Selected genes were measured by real-time reverse transcriptase PCR in CTCs of 50 metastatic breast cancer patients collected before starting first-line systemic therapy in blood from 53 healthy blood donors (HBD) and in primary tumors of 8 of the patients. The molecular profiles were associated with CTC counts and clinical parameters and compared with the profiles generated from the corresponding primary tumors. RESULTS: We identified 55 mRNAs and 10 miRNAs more abundantly expressed in samples from 32 patients with at least 5 CTCs in 7.5 mL of blood compared with samples from 9 patients without detectable CTCs and HBDs. Clustering analysis resulted in 4 different patient clusters characterized by 5 distinct gene clusters. Twice the number of patients from cluster 2 to 4 had developed both visceral and nonvisceral metastases. Comparing transcript levels in CTCs with those measured in corresponding primary tumors showed clinically relevant discrepancies in estrogen receptor and HER2 levels. CONCLUSIONS: Our study shows that molecular profiling of low numbers of CTCs in a high background of leukocytes is feasible and shows promise for further studies on the clinical relevance of molecular characterization of CTCs.

Copy number alterations that predict metastatic capability of human breast cancer.

We have analyzed the DNA copy numbers for over 100,000 single-nucleotide polymorphism loci across the human genome in genomic DNA from 313 lymph node-negative primary breast tumors for which genome-wide gene expression data were also available. Combining these two data sets allowed us to identify the genomic loci and their mapped genes, having high correlation with distant metastasis. An estimation of the likely response based on published predictive signatures was performed in the identified prognostic subgroups defined by gene expression and DNA copy number data. In the training set of 200 patients, we constructed an 81-gene prognostic copy number signature (CNS) that identified a subgroup of patients with increased probability of distant metastasis in the independent validation set of 113 patients [hazard ratio (HR), 2.8; 95% confidence interval (95% CI), 1.4-5.6] and in an external data set of 116 patients (HR, 3.7; 95% CI, 1.3-10.6). These high-risk patients constituted a subset of the high-risk patients predicted by our previously established 76-gene gene expression signature (GES). This very poor prognostic group identified by CNS and GES was putatively more resistant to preoperative paclitaxel and 5-fluorouracil-doxorubicin-cyclophosphamide combination chemotherapy (P = 0.0048), particularly against the doxorubicin compound, while potentially benefiting from etoposide. Our study shows the feasibility of using copy number alterations to predict patient prognostic outcome. When combined with gene expression-based signatures for prognosis, the CNS refines risk classification and can help identify those breast cancer patients who have a significantly worse outlook in prognosis and a potential differential response to chemotherapeutic drugs.