miR148b is a major coordinator of breast cancer progression in a relapse-associated microRNA signature by targeting ITGA5, ROCK1, PIK3CA, NRAS, and CSF1.

Breast cancer is often fatal during its metastatic dissemination. To unravel the role of microRNAs (miRs) during malignancy, we analyzed miR expression in 77 primary breast carcinomas and identified 16 relapse-associated miRs that correlate with survival and/or distinguish tumor subtypes in different datasets. Among them, miR-148b, down-regulated in aggressive breast tumors, was found to be a major coordinator of malignancy. In fact, it is able to oppose various steps of tumor progression when overexpressed in cell lines by influencing invasion, survival to anoikis, extravasation, lung metastasis formation, and chemotherapy response. miR-148b controls malignancy by coordinating a novel pathway involving over 130 genes and, in particular, it directly targets players of the integrin signaling, such as ITGA5, ROCK1, PIK3CA/p110α, and NRAS, as well as CSF1, a growth factor for stroma cells. Our findings reveal the importance of the identified 16 miRs for disease outcome predictions and suggest a critical role for miR-148b in the control of breast cancer progression.

Microvesicles released from human renal cancer stem cells stimulate angiogenesis and formation of lung premetastatic niche.

Recent studies suggest that tumor-derived microvesicles (MV) act as a vehicle for exchange of genetic information between tumor and stromal cells, engendering a favorable microenvironment for cancer development. Within the tumor mass, all cell types may contribute to MV shedding, but specific contributions to tumor progression have yet to be established. Here we report that a subset of tumor-initiating cells expressing the mesenchymal stem cell marker CD105 in human renal cell carcinoma releases MVs that trigger angiogenesis and promote the formation of a premetastatic niche. MVs derived only from CD105-positive cancer stem cells conferred an activated angiogenic phenotype to normal human endothelial cells, stimulating their growth and vessel formation after in vivo implantation in immunocompromised severe combined immunodeficient (SCID) mice. Furthermore, treating SCID mice with MVs shed from CD105-positive cells greatly enhanced lung metastases induced by i.v. injection of renal carcinoma cells. Molecular characterization of CD105-positive MVs defines a set of proangiogenic mRNAs and microRNAs implicated in tumor progression and metastases. Our results define a specific source of cancer stem cell-derived MVs that contribute to triggering the angiogenic switch and coordinating metastatic diffusion during tumor progression.

A signature inferred from Drosophila mitotic genes predicts survival of breast cancer patients.

INTRODUCTION: The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures. METHODS: We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes). RESULTS: The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis. CONCLUSION: This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies.

Prediction of human disease genes by human-mouse conserved coexpression analysis.

BACKGROUND: Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. METHODOLOGY/PRINCIPAL FINDINGS: We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. CONCLUSION: Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes.