Microarray-based analysis of single nucleotide polymorphisms (SNPs) has many applications in large-scale genetic studies. To minimize the influence of experimental variation, microarray data usually need to be processed in different aspects including background subtraction, normalization and low-signal filtering before genotype determination. Although many algorithms are sophisticated for these purposes, biases are still present. In the present paper, new algorithms for SNP microarray data analysis and the software, AccuTyping, developed based on these algorithms are described. The algorithms take advantage of a large number of SNPs included in each assay, and the fact that the top and bottom 20% of SNPs can be safely treated as homozygous after sorting based on their ratios between the signal intensities. These SNPs are then used as controls for color channel normalization and background subtraction. Genotype calls are made based on the logarithms of signal intensity ratios using two cutoff values, which were determined after training the program with a dataset of ∼160 000 genotypes and validated by non-microarray methods. AccuTyping was used to determine >300 000 genotypes of DNA and sperm samples. The accuracy was shown to be >99%. AccuTyping can be downloaded from http://www2.umdnj.edu/lilabweb/publications/AccuTyping.html.

MicroRNAs are small non-coding RNA molecules that can regulate gene expression by interacting with multiple mRNAs and inducing either translation suppression or degradation of mRNA. Recently, several miRNAs were identified as either promoters or suppressors of metastasis. However, it is unclear in which step(s) of the multistep metastatic cascade these miRNAs play a defined functional role. To study the functional importance of miRNAs in epithelial-mesenchymal transition (EMT), a process thought to initiate metastasis by enhancing the motility of tumor cells, we used a well established in vitro EMT assay: transforming growth factor-β-induced EMT in NMuMG murine mammary epithelial cells. We found that members of the miR-200 family, organized as two clusters in the genome, were repressed during EMT. Overexpression of each miRNA individually or as clusters in NMuMG cells hindered EMT by enhancing E-cadherin expression through direct targeting of ZEB1 and ZEB2, which encode transcriptional repressors of E-cadherin. In the 4TO7 mouse carcinoma cell line, which expresses low levels of endogenous E-cadherin and displays a mesenchymal phenotype, ectopic expression of the miR-200 family miRNAs significantly increased E-cadherin expression and altered cell morphology to an epithelial phenotype. Furthermore, ectopic expression of each miR-200 miRNA cluster significantly reduced the in vitro motility of 4TO7 cells in migration assays. These results suggested that loss of expression of the miR-200 family members may play a critical role in the repression of E-cadherin by ZEB1 and ZEB2 during EMT, thereby enhancing migration and invasion during cancer progression.

Background Rapid progress in the field of gene expression-based molecular network integration has generated strong demand on enhancing the sensitivity and data accuracy of experimental systems. To meet the need, a high-throughput gene profiling system of high specificity and sensitivity has been developed. Results By using specially designed primers, the new system amplifies sequences in neighboring exons separated by big introns so that mRNA sequences may be effectively discriminated from other highly related sequences including their genes, unprocessed transcripts, pseudogenes and pseudogene transcripts. Probes used for microarray detection consist of sequences in the two neighboring exons amplified by the primers. In conjunction with a newly developed high-throughput multiplex amplification system and highly simplified experimental procedures, the system can be used to analyze >1,000 mRNA species in a single assay. It may also be used for gene expression profiling of very few (n = 100) or single cells. Highly reproducible results were obtained from duplicate samples with the same number of cells, and from those with a small number (100) and a large number (10,000) of cells. The specificity of the system was demonstrated by comparing results from a breast cancer cell line, MCF-7, and an ovarian cancer cell line, NCI/ADR-RES, and by using genomic DNA as starting material. Conclusion Our approach may greatly facilitate the analysis of combinatorial expression of known genes in many important applications, especially when the amount of RNA is limited.

Bone metastasis is mediated by complex interactions between tumor cells and resident stromal cells in the bone microenvironment. The functions of metalloproteinases in organ-specific metastasis remain poorly defined despite their well-appreciated role in matrix degradation and tumor invasion. Here, we show a mechanism whereby two distinct metalloproteinases, a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS1) and matrix metalloproteinase-1 (MMP1), orchestrate a paracrine signaling cascade to modulate the bone microenvironment in favor of osteoclastogenesis and bone metastasis. Proteolytic release of membrane-bound epidermal growth factor (EGF)-like growth factors, including Amphiregulin (AREG), heparin-binding EGF (HB-EGF), and transforming growth factor α (TGFα) from tumor cells suppress the expression of osteoprotegerin (OPG) in osteoblasts and subsequently potentiate osteoclast differentiation. EGF receptor (EGFR) inhibitors block osteolytic bone metastasis by targeting EGFR signaling in bone stromal cells. Furthermore, elevated MMP1 and ADAMTS1 expression is associated with increased risk of bone metastasis in breast cancer patients. This study established MMP1 and ADAMTS1 in tumor cells, as well as EGFR signaling in osteoblasts, as promising therapeutic targets for inhibiting bone metastasis of breast cancer.

Targeted therapy for metastatic diseases relies on the identification of functionally important metastasis genes from a large number of random genetic alterations. Here we use a computational algorithm to map minimal recurrent genomic alterations associated with poor-prognosis breast cancer. 8q22 genomic gain was identified by this approach and validated in an extensive collection of breast tumor samples. Regional gain of 8q22 elevates expression of the metastasis gene metadherin (MTDH), which is overexpressed in more than 40% of breast cancers and is associated with poor clinical outcomes. Functional characterization of MTDH revealed its dual role in promoting metastatic seeding and enhancing chemoresistance. These findings establish MTDH as an important therapeutic target for simultaneously enhancing chemotherapy efficacy and reducing metastasis risk.