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. 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. 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. One of the most limiting aspects of biological research in the post-genomic era is the capability to integrate massive datasets on gene structure and function for producing useful biological knowledge. In this report we have applied an integrative approach to address the problem of identifying likely candidate genes within loci associated with human genetic diseases. Despite the recent progress in sequencing technologies, approaching this problem from an experimental perspective still represents a very demanding task, because the critical region may typically contain hundreds of positional candidates. We found that by concentrating only on genes sharing similar expression profiles in both human and mouse, massive microarray datasets can be used to reliably identify disease-relevant relationships among genes. Moreover, we found that integrating the coexpression criterion with systematic phenome analysis allows efficient identification of disease genes in large genomic regions. Using this approach on 850 OMIM loci characterized by unknown molecular basis, we propose high-probability candidates for 81 genetic diseases.

Malignant melanoma is one of the most aggressive human cancers, but the mechanisms governing its metastatic dissemination are not fully understood. Upregulation of miR-214 and ALCAM and the loss of TFAP2 expression have been implicated in this process, with TFAP2 a direct target of miR-214. Here, we link miR-214 and ALCAM as well as identify a core role for miR-214 in organizing melanoma metastasis. miR-214 upregulated ALCAM, acting transcriptionally through TFAP2 and also posttranscriptionally through miR-148b (itself controlled by TFAP2), both negative regulators of ALCAM. We also identified several miR-214–mediated prometastatic functions directly promoted by ALCAM. Silencing ALCAM in miR-214–overexpressing melanoma cells reduced cell migration and invasion without affecting growth or anoikis in vitro, and it also impaired extravasation and metastasis formation in vivo. Conversely, cell migration and extravasation was reduced in miR-214–overexpressing cells by upregulation of either miR-148b or TFAP2. These findings were consistent with patterns of expression of miR-214, ALCAM, and miR-148b in human melanoma specimens. Overall, our results define a pathway involving miR-214, miR-148b, TFAP2, and ALCAM that is critical for establishing distant metastases in melanoma. Cancer Res; 73(13); 4098–111. ©2013 AACR.

MiR-214 and miR-148b have been proposed to antagonize the effects of each other in enabling or blocking metastasis, respectively. In this study, we provide evidence deepening their role and interrelationship in the process of metastatic dissemination. Depleting miR-214 or elevating miR-148b blocked the dissemination of melanoma or breast cancer cells, an effect that could be accentuated by dual alteration. Mechanistic investigations indicated that dual alteration suppressed passage of malignant cells through the blood vessel endothelium by reducing expression of the cell adhesion molecules ITGA5 and ALCAM. Notably, transendothelial migration in vitro and extravasation in vivo impaired by singly alternating miR-214 or miR-148b could be overridden by overexpression of ITGA5 or ALCAM in the same tumor cells. In clinical specimens of primary breast cancer or metastatic melanoma, we found a positive correlation between miR-214 and ITGA5 or ALCAM along with an inverse correlation of miR-214 and miR-148b in the same specimens. Our findings define an antagonistic relationship of miR-214 and miR-148b in determining the dissemination of cancer cells via tumor–endothelial cell interactions, with possible implications for microRNA-mediated therapeutic interventions aimed at blocking cancer extravasation. Cancer Res; 76(17); 5151–62. ©2016 AACR.

Drug tolerance in EGFR-inhibited mCRC involves secretory pseudodifferentiation and rewiring of oncogenic dependencies.