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Background Prostate cancer is one of the most common and socially significant cancers among men. The aim of our study was to reveal changes in miRNA expression profiles associated with lymphatic dissemination in prostate cancer and to identify the most prominent miRNAs as potential prognostic markers for future studies. Methods High-throughput miRNA sequencing was performed for 44 prostate cancer specimens taken from Russian patients, with and without lymphatic dissemination (N1 – 20 samples; N0 – 24 samples). Results We found at least 18 microRNAs with differential expression between N0 and N1 sample groups: miR-182-5p, miR-183-5p, miR-96-5p, miR-25-3p, miR-93-5p, miR-7-5p, miR-615-3p, miR-10b, miR-1248 (N1-miRs; elevated expression in N1 cohort; p miR-1271-5p, miR-184, miR-222-3p, miR-221-5p, miR-221-3p, miR-455-3p, miR-143-5p, miR-181c-3p and miR-455-5p (N0-miRs; elevated expression in N0; p . The expression levels of N1-miRs were highly correlated between each other (the same is applied for N0-miRs) and the expression levels of N0-miRs and N1-miRs were anti-correlated. The tumor samples can be divided into two groups depending on the expression ratio between N0-miRs and N1-miRs. Conclusions We found the miRNA expression signature associated with lymphatic dissemination, in particular on the Russian patient cohort. Many of these miRNAs are well-known players in either oncogenic transformation or tumor suppression. Further experimental studies with extended sampling are required to validate these results.

Background Carotid paragangliomas (CPGLs) are rare neuroendocrine tumors that arise from the paraganglion at the bifurcation of the carotid artery and are responsible for approximately 65% of all head and neck paragangliomas. CPGLs can occur sporadically or along with different hereditary tumor syndromes. Approximately 30 genes are known to be associated with CPGLs. However, the genetic basis behind the development of these tumors is not fully elucidated, and the molecular mechanisms underlying CPGL pathogenesis remain unclear. Methods Whole exome and transcriptome high-throughput sequencing of CPGLs was performed on an Illumina platform. Exome libraries were prepared using a Nextera Rapid Capture Exome Kit (Illumina) and were sequenced under 75 bp paired-end model. For cDNA library preparation, a TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Gold (Illumina) was used; transcriptome sequencing was carried out with 100 bp paired-end read length. Obtained data were analyzed using xseq which estimates the influence of mutations on gene expression profiles allowing to identify potential causative genes. Results We identified a total of 16 candidate genes (MYH15, CSP1, MYH3, PTGES3L, CSGALNACT2, NMD3, IFI44, GMCL1, LSP1, PPFIBP2, RBL2, MAGED1, CNIH3, STRA6, SLC6A13, and ATM) whose variants potentially influence their expression (cis-effect). The strongest cis-effect of loss-of-function variants was found in MYH15, CSP1, and MYH3, and several likely pathogenic variants in these genes associated with CPGLs were predicted. Conclusions Using the xseq probabilistic model, three novel potential causative genes, namely MYH15, CSP1, and MYH3, were identified in carotid paragangliomas.

Background Carotid body tumor (CBT) is a form of head and neck paragangliomas (HNPGLs) arising at the bifurcation of carotid arteries. Paragangliomas are commonly associated with germline and somatic mutations involving at least one of more than thirty causative genes. However, the specific functionality of a number of these genes involved in the formation of paragangliomas has not yet been fully investigated. Methods Exome library preparation was carried out using Nextera® Rapid Capture Exome Kit (Illumina, USA). Sequencing was performed on NextSeq 500 System (Illumina). Results Exome analysis of 52 CBTs revealed potential driver mutations (PDMs) in 21 genes: ARNT, BAP1, BRAF, BRCA1, BRCA2, CDKN2A, CSDE1, FGFR3, IDH1, KIF1B, KMT2D, MEN1, RET, SDHA, SDHB, SDHC, SDHD, SETD2, TP53BP1, TP53BP2, and TP53I13. In many samples, more than one PDM was identified. There are also 41% of samples in which we did not identify any PDM; in these cases, the formation of CBT was probably caused by the cumulative effect of several not highly pathogenic mutations. Estimation of average mutation load demonstrated 6–8 mutations per megabase (Mb). Genes with the highest mutation rate were identified. Conclusions Exome analysis of 52 CBTs for the first time revealed the average mutation load for these tumors and also identified potential driver mutations as well as their frequencies and co-occurrence with the other PDMs. Electronic supplementary material The online version of this article (10.1186/s12920-018-0327-0) contains supplementary material, which is available to authorized users.

Background Neuropilin and tolloid-like 2 (NETO2) is a single-pass transmembrane protein that has been shown primarily implicated in neuron-specific processes. Upregulation of NETO2 gene was also detected in several cancer types. In colorectal cancer (CRC), it was associated with tumor progression, invasion, and metastasis, and seems to be involved in epithelial-mesenchymal transition (EMT). However, the mechanism of NETO2 action is still poorly understood. Results We have revealed significant increase in the expression of NETO2 gene and deregulation of eight EMT-related genes in CRC. Four of them were upregulated (TWIST1, SNAIL1, LEF1, and FOXA2); the mRNA levels of other genes (FOXA1, BMP2, BMP5, and SMAD7) were decreased. Expression of NETO2 gene was weakly correlated with that of genes involved in the EMT process. Conclusions We found considerable NETO2 upregulation, but no significant correlation between the expression of NETO2 and EMT-related genes in CRC. Thus, NETO2 may be involved in CRC progression, but is not directly associated with EMT.