Mir-660 is downregulated in lung cancer patients and its replacement inhibits lung tumorigenesis by targeting MDM2-p53 interaction.

Lung cancer represents the leading cause of cancer-related death in developed countries. Despite the advances in diagnostic and therapeutic techniques, the 5-year survival rate remains low. The research for novel therapies directed to biological targets has modified the therapeutic approach, but the frequent engagement of resistance mechanisms and the substantial costs, limit the ability to reduce lung cancer mortality. MicroRNAs (miRNAs) are small noncoding RNAs with known regulatory functions in cancer initiation and progression. In this study we found that mir-660 expression is downregulated in lung tumors compared with adjacent normal tissues and in plasma samples of lung cancer patients with poor prognosis, suggesting a potential functional role of this miRNA in lung tumorigenesis. Transient and stable overexpression of mir-660 using miRNA mimics reduced migration, invasion, and proliferation properties and increased apoptosis in p53 wild-type lung cancer cells (NCI-H460, LT73, and A549). Furthermore, stable overexpression using lentiviral vectors in NCI-H460 and A549 cells inhibited tumor xenograft growth in immunodeficient mice (95 and 50% reduction compared with control, respectively), whereas the effects of mir-660 overexpression were absent in H1299, a lung cancer cell line lacking p53 locus, both in in vitro and in vivo assays. We identified and validated mouse double minute 2 (MDM2) gene, a key regulator of the expression and function of p53, as a new direct target of mir-660. In addition, mir-660 expression reduced both mRNA and protein expression of MDM2 in all cell lines and stabilized p53 protein levels resulting in an upregulation of p21(WAF1/CIP1) in p53 wild-type cells. Our finding supports that mir-660 acts as a tumor suppressor miRNA and we suggest the replacement of mir-660 as a new therapeutic approach for p53 wild-type lung cancer treatment.

Unclassified variants in BRCA genes: guidelines for interpretation.

In the last few years, several studies have focused on the interpretation of unclassified variants (UVs) of BRCA1 and BRCA2 genes. Analysis of UVs through a unique approach is not sufficient to understand their role in the development of tumors. Thus, it is clear that assembling results from different sources (genetic and epidemiological data, histopathological features, and in vitro and in silico analyses) represents a powerful way to classify such variants. Building reliable integrated models for UV classification requires the joining of many working groups to collaborative consortia, allowing data exchange and improvements of methods. This will lead to improvement in the predictivity of gene testing in BRCA1 and BRCA2 and, consequently, to an increase in the number of families that can be correctly classified as linked or unlinked to these genes, allowing more accurate genetic counseling and clinical management.