BackgroundRecently copy number variation (CNV) has gained considerable interest as a type of genomic/genetic variation that plays an important role in disease susceptibility. Advances in sequencing technology have created an opportunity for detecting CNVs more accurately. Recently whole exome sequencing (WES) has become primary strategy for sequencing patient samples and study their genomics aberrations. However, compared to whole genome sequencing, WES introduces more biases and noise that make CNV detection very challenging. Additionally, tumors’ complexity makes the detection of cancer specific CNVs even more difficult. Although many CNV detection tools have been developed since introducing NGS data, there are few tools for somatic CNV detection for WES data in cancer.ResultsIn this study, we evaluated the performance of the most recent and commonly used CNV detection tools for WES data in cancer to address their limitations and provide guidelines for developing new ones. We focused on the tools that have been designed or have the ability to detect cancer somatic aberrations. We compared the performance of the tools in terms of sensitivity and false discovery rate (FDR) using real data and simulated data. Comparative analysis of the results of the tools showed that there is a low consensus among the tools in calling CNVs. Using real data, tools show moderate sensitivity (~50% - ~80%), fair specificity (~70% - ~94%) and poor FDRs (~27% - ~60%). Also, using simulated data we observed that increasing the coverage more than 10× in exonic regions does not improve the detection power of the tools significantly.ConclusionsThe limited performance of the current CNV detection tools for WES data in cancer indicates the need for developing more efficient and precise CNV detection methods. Due to the complexity of tumors and high level of noise and biases in WES data, employing advanced novel segmentation, normalization and de-noising techniques that are designed specifically for cancer data is necessary. Also, CNV detection development suffers from the lack of a gold standard for performance evaluation. Finally, developing tools with user-friendly user interfaces and visualization features can enhance CNV studies for a broader range of users.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1705-x) contains supplementary material, which is available to authorized users.

MicroRNAs (miRNAs) are small non-coding RNAs that negatively regulate gene expression post-transcriptionally. They are crucial for normal development and maintaining homeostasis. Researchers have discovered that dysregulated miRNA expression contributes to many pathological conditions, including cancer. miRNAs can augment or suppress tumorigenesis based on their expression and transcribed targetome in various cell types. In recent years, researchers have begun to identify miRNAs commonly dysregulated in cancer. One recently identified miRNA, miR-708-5p, has been shown to have profound roles in promoting or suppressing oncogenesis in a myriad of solid and hematological tumors. This review highlights the diverse, sometimes controversial findings reported for miR-708-5p in cancer, and the importance of further exploring this exciting miRNA.

Arachidonic acid (AA) can be converted into prostaglandins (PGs) or leukotrienes (LTs) by the enzymatic actions of cyclooxygenases (COX-1 and COX-2) or 5-lipoxygenase (5-LO), respectively. PGs and LTs are lipid signaling molecules that have been implicated in various diseases, including multiple cancers. 5-LO and its activating protein (FLAP) work together in the first two conversion steps of LT production. Previous work has suggested a role for LTs in cancer development and progression. MicroRNAs (miRNAs) are small RNA molecules that negatively regulate gene expression post-transcriptionally, and have previously been shown to be involved in cancer. Here, we show that high FLAP expression is associated with lower overall survival in lung adenocarcinoma patients, and FLAP protein is overexpressed in lung cancer cells compared to normal lung cells. Our lab has previously shown that miR-146a regulates COX-2 in lung cancer cells, and this miRNA is also predicted to target FLAP. Transient and stable transfections of miR-146a repress endogenous FLAP expression in lung cancer cells, and reporter assays show this regulation occurs through a direct interaction between the FLAP 3′ untranslated region (UTR) and miR-146a. Restoration of miR-146a also results in decreased cancer cell Leukotriene B4 (LTB4) production. Additionally, methylation analysis indicates the miR-146a promoter is hypermethylated in lung cancer cell lines. Taken together, this study and previous work from our lab suggest miR-146a is an endogenous dual inhibitor of AA metabolism in lung cancer cells by regulating both PG and LT production through direct targeting of the COX-2 and FLAP 3’ UTRs.

Many cancers maintain an inflammatory microenvironment to promote their growth. Lung cancer is of particular importance, as it is the deadliest cancer worldwide. One inflammatory pathway commonly dysregulated in cancer is the metabolism of arachidonic acid (AA) by Cyclooxygenase-2 (COX-2) and microsomal Prostaglandin E Synthase 1 (mPGES-1) into Prostaglandin E2 (PGE 2 ). While researchers have identified PGE 2 's pro-tumorigenic functions, the mechanisms governing overexpression of COX-2 and mPGES-1 are incompletely understood. MicroRNAs (miRNAs) are important posttranscriptional regulators commonly dysregulated in cancer. Interestingly, miR-708-5p (miR-708) is predicted to target both COX-2 and mPGES-1. In this study, we show that high miR-708 expression is associated with survival rates in lung squamous cell carcinoma patients. miR-708 also represses PGE 2 production by suppressing both COX-2 and mPGES-1 expression in lung cancer cells. miR-708 regulation of COX-2 and mPGES-1 is mediated through targeting of their 3′ untranslated regions (UTRs). Moreover, miR-708 decreases proliferation, survival, and migration of lung cancer cells, which can be partially attributed to miR-708's inhibition of PGE 2 signaling. Lastly, we identify novel miR-708 predicted targets and possible regulators of miR-708 expression in lung cancer. Collectively, these data demonstrate that dysregulated miR-708 expression contributes to exacerbated PGE 2 production, leading to an enhanced pro-tumorigenic phenotype in lung cancer cells.