It is widely accepted that most colorectal cancers (CRCs) arise from colorectal adenomas (CRAs), but transcriptomic data characterizing the progression from colorectal normal mucosa to adenoma, and then to adenocarcinoma are scarce. These transition steps were investigated using microarrays, both at the level of gene expression and alternative pre-mRNA splicing. Many genes and exons were abnormally expressed in CRAs, even more than in CRCs, as compared to normal mucosae. Known biological pathways involved in CRC were altered in CRA, but several new enriched pathways were also recognized, such as the complement and coagulation cascades. We also identified four intersectional transcriptional signatures that could distinguish CRAs from normal mucosae or CRCs, including a signature of 40 genes differentially deregulated in both CRA and CRC samples. A majority of these genes had been described in different cancers, including FBLN1 or INHBA, but only a few in CRC. Several of these changes were also observed at the protein level. In addition, 20% of these genes (i.e. CFH, CRYAB, DPT, FBLN1, ITIH5, NR3C2, SLIT3 and TIMP1) showed altered pre-mRNA splicing in CRAs. As a global variation occurring since the CRA stage, and maintained in CRC, the expression and splicing changes of this 40-gene set may mark the risk of cancer occurrence from analysis of CRA biopsies.
Alternative pre-mRNA splicing (AS) widely expands proteome diversity through the combinatorial assembly of exons. The analysis of AS on a large scale, by using splice-sensitive microarrays, is a highly efficient method to detect the majority of known and predicted alternative transcripts for a given gene. The response to targeted anticancer therapies cannot easily be anticipated without prior knowledge of the expression, by the tumor, of target proteins or genes. To analyze, in depth, transcript structure and levels for genes involved in these responses, including AKT1-3, HER1-4, HIF1A, PIK3CA, PIK3R1-2, VEGFA-D and PIR, we engineered a dedicated gene chip with coverage of an average 185 probes per gene and, especially, exon-exon junction probes. As a proof of concept, we demonstrated the ability of such a chip to detect the effects of over-expressed SRSF2 RNA binding protein on the structure and abundance of mRNA products in H358 lung cancer cells conditionally over-expressing SRSF2. Major splicing changes were observed, including in HER1/EGFR pre-mRNA, which were also seen in human lung cancer samples over-expressing the SRSF2 protein. In addition, we showed that variations in HER1/EGFR pre-mRNA splicing triggered by SRSF2 overexpression in H358 cells resulted in a drop in HER1/EGFR protein level, which correlated with increased sensitivity to gefitinib, an EGFR tyrosine kinase inhibitor. We propose, therefore, that this novel tool could be especially relevant for clinical applications, with the aim to predict the response before treatment.
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