BackgroundColorectal cancer (CRC) is a common cancer worldwide. The main cause of death in CRC includes tumor progression and metastasis. At molecular level, these processes may be triggered by epithelial-mesenchymal transition (EMT) and necessitates specific alterations in cell metabolism. Although several EMT-related metabolic changes have been described in CRC, the mechanism is still poorly understood.ResultsUsing CrossHub software, we analyzed RNA-Seq expression profile data of CRC derived from The Cancer Genome Atlas (TCGA) project. Correlation analysis between the change in the expression of genes involved in glycolysis and EMT was performed. We obtained the set of genes with significant correlation coefficients, which included 21 EMT-related genes and a single glycolytic gene, HK3. The mRNA level of these genes was measured in 78 paired colorectal cancer samples by quantitative polymerase chain reaction (qPCR). Upregulation of HK3 and deregulation of 11 genes (COL1A1, TWIST1, NFATC1, GLIPR2, SFPR1, FLNA, GREM1, SFRP2, ZEB2, SPP1, and RARRES1) involved in EMT were found. The results of correlation study showed that the expression of HK3 demonstrated a strong correlation with 7 of the 21 examined genes (ZEB2, GREM1, TGFB3, TGFB1, SNAI2, TWIST1, and COL1A1) in CRC.ConclusionsUpregulation of HK3 is associated with EMT in CRC and may be a crucial metabolic adaptation for rapid proliferation, survival, and metastases of CRC cells.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4477-4) contains supplementary material, which is available to authorized users.
BackgroundColorectal cancer (CRC) is one of the most common malignant tumors worldwide. CRC molecular pathogenesis is heterogeneous and may be followed by mutations in oncogenes and tumor suppressor genes, chromosomal and microsatellite instability, alternative splicing alterations, hypermethylation of CpG islands, oxidative stress, impairment of different signaling pathways and energy metabolism. In the present work, we have studied the alterations of alternative splicing patterns of genes related to energy metabolism in CRC.ResultsUsing CrossHub software, we analyzed The Cancer Genome Atlas (TCGA) RNA-Seq datasets derived from colon tumor and matched normal tissues. The expression of 1014 alternative mRNA isoforms involved in cell energy metabolism was examined. We found 7 genes with differentially expressed alternative transcripts whereas overall expression of these genes was not significantly altered in CRC. A set of 8 differentially expressed transcripts of interest has been validated by qPCR. These eight isoforms encoded by OGDH, COL6A3, ICAM1, PHPT1, PPP2R5D, SLC29A1, and TRIB3 genes were up-regulated in colorectal tumors, and this is in concordance with the bioinformatics data. The alternative transcript NM_057167 of COL6A3 was also strongly up-regulated in breast, lung, prostate, and kidney tumors. Alternative transcript of SLC29A1 (NM_001078177) was up-regulated only in CRC samples, but not in the other tested tumor types.ConclusionsWe identified tumor-specific expression of alternative spliced transcripts of seven genes involved in energy metabolism in CRC. Our results bring new knowledge on alternative splicing in colorectal cancer and suggest a set of mRNA isoforms that could be used for cancer diagnosis and development of treatment methods.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3351-5) contains supplementary material, which is available to authorized users.
BackgroundCarotid 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.MethodsExome library preparation was carried out using Nextera® Rapid Capture Exome Kit (Illumina, USA). Sequencing was performed on NextSeq 500 System (Illumina).ResultsExome 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.ConclusionsExome 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 materialThe online version of this article (10.1186/s12920-018-0327-0) contains supplementary material, which is available to authorized users.
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