PO-275 Gene expression and splicing variants changes in colorectal cancer related cell function pathways

Abstract

IntroductionIn addition to expression level analysis, gene splicing variant determination is also technically available now on microarrays and by RNA sequencing. In this study colorectal cancer related gene expression, gene splicing analysis performed with Kegg pathway and gene ontology evaluation with protein interaction network evaluation.Material and methodsBiopsy samples after collection were immediately put in stabilisation reagent and stored at −80°C from healthy colonic normal (n=20) and malignant biopsy specimen (n=20). Human Transcriptome Microarrays (HTA 2.0) washed, scanned and analysed. Gene +Exon SST-RMA summarization was performed by Affymetrix TAC 4.0 software. In silico analysis was performed from the GEO database (GSE73360), in which 37 CRC biopsies from 27 patients, and 19 NAT biopsies (3–6 cm away from the tumour) were collected. Differently expressed genes from normal versus cancer pairwise comparison were determined and three transcript set variants were first defined. Transcripts with significant (>abs 2) fold changes and with exon-splicing events were in transcript set 1. Low level fold changes (<abs 2) with exon-splicing event characterised the transcript set 2. Transcript set 3 was characterised by increased fold changes (>abs 2) but without any exon-splicing event. For KEGG and GO analysis DAVID while for key control gene determinations STRING ppi network was applied.Results and discussionsGEO in silico confirmation was applied before pathway analysis. For transcript set 1 five clusters of genes were determined, which involved into the most common pathways such as RNA transport (NUP43, 107 and 205) and Cell cycle (MCM3, 5 and 7). For transcript set 2 one clusters of genes were determined which involved pathways were Epstein-Barr virus infection (CD39, IRAK1 and POLR3H), Ribosome biogenesis in eukaryotes (GAR1, IMP4 and RAN), Purine and Pyrimidine metabolism (POLD2 and POLR1B) pathways. For transcript set 3 four clusters of genes were determined Cell cycle (CCNA2, CCNB1, RBL1 and TFDP1) and 3 in PPAR signalling pathway (ACSL4, MMP1 and SCD2).ConclusionDifferent splicing transcript variants, in addition to their expression level alterations may play important role in CRC cancer pathways. Splicing events with or without fold changes participate in additional signal transduction processes in CRC development like nucleotide metabolism.