Aberrant pre-mRNA splicing may be an important epigenetic factor for tumor progression. However, it is unclear how many genes are mis-spliced in a given tumor and whether aberrant expression of splice factors is responsible for their appearance. We used an exon array and designed analytical algorithms and parameters to identify GBM-specific splicing events in an unbiased manner. By plotting scores for differential expression (DE) against those for alternative splicing (AS) for genes and exons interrogated by the exon array, we were able to distinguish a single targeted induced splicing change in FGFR1 among 20,157 RefSeq entries and to monitor the concomitant splicing and gene expression changes. Using the same approach for comparing an extended GBM and nontumor sample set, GBM-specific splicing events of similar magnitude were not identified, which suggests that large-scale aberrant splicing in GBM are infrequent. We do not discount the fact that individual instances of dramatic changes in splicing were present; however, they were not shared by the majority of samples. The lack of events with large changes in differential exon expression led us to mine our data for splicing changes with at least a 2-fold change in probe set hybridization (AS score) and a p-value < 0.05. In the hundreds of heatmaps examined, there were many changes indicative of the usage of alternative promoters or polyadenylation sites. However, we chose to focus on cassette exons as events that could be readily examined by RT-PCR. This led to the validation of 14 GBM-specific events: A2BP1, APPA4, BCAS1, CACNA1G, CALD1, CLTA,CLTB, DYNC1I2, KCNC2, NF1, RTN4, SNCB, TNC and TPD52L2. Moreover, our expression profiling analysis indicated that there were relatively few GBM-specific changes for splicing regulators. Among the genes with the greatest differential expression only A2BP1, CUGBP2, ELAV1, MBNL2, PTBP1 and YBX1, have known functions in alternative splicing. At least three of these (A2BP1, PTBP1 and CUGBP2) could be linked to GBM-specific splicing events.
The identified and validated GBM-specific isoforms encode proteins that primarily affect cell growth and mobility. A2BP1, which shows both differential expression and splicing, is a neuronal-specific splicing regulator for multiple targets [36
]. CLTB and DYNC1I2 are involved in intracellular transport and may play a role in cell migration [37
]. Four genes have clearly identified functions in the central nervous system: APPA4 functions in Notch signaling during neural development, cell adhesion and apoptosis; RTN4 is a neurite growth inhibitor; and SNCB, which is upregulated in glial tumors, is thought to regulate phospholipase D2 activity. NF1 is believed to be a glial-cell marker and mutated in multiple CNS tumors [14
]. For the remaining genes, little is known about their function in normal brain or gliomagenesis. Comparing glioblastoma and oligodendroglioma as two histological glioma subgroups on the same exon array platform that we used here, French and colleagues recently identified a total of 11 differentially expressed splice variants [40
], one of which overlapped with our validated genes (CAMK2A
) (see Additional file 1
). In the exon array study for prostate and colon cancer, only CALD1
was in common with our validated gene list [29
]. Therefore, it is unclear whether common pathways are targeted for splicing changes during tumorigenesis. It remains to be determined whether these splicing targets have a synergistic effect on gliomagenesis.
Genes with glioma-predominant splice isoforms have previously been identified through global EST alignments. MAX
was the only gene found both experimentally and in silico
(see Additional files 1
). Despite using similar datasets, the number of in silico
derived genes with GBM-specific isoforms varied and only three genes were found to be shared between two of the five studies: AP2A1
]. The lack of agreement between all of these studies can be explained by several technical and biological factors. First, the small sample sizes used did not allow for statistical calculations. Second, sample heterogeneity affected normalization and interpretation. Third, the nature of the samples being compared, which can be normal or nontumor vs
. tumor, or tumor type A vs
. tumor type B. For EST libraries, the true splicing frequency could be masked by too few ESTs, normalization strategies, and/or low-stringency criteria that enriched for rare ESTs [41
]. The bias towards 3' and 5' ends of transcripts could also lead to the under-representation of isoforms with internal differences [41
]. In contrast, using a large sample set on exon arrays circumvented these problems and allowed for objective measurements of isoform frequencies. It should be noted, however, that array-based studies are limited by the quality of the target preparation, probe specificity and sensitivity, and for the Affymetrix platform we used the lack of interrogation of exons < 25 bp., and can be confounded by tumor tissue heterogeneity. Of our 14 validated GBM-associated splicing events, eight (CAMK2A
) were previously reported (see Additional files 1
). Most of the genes that were discordant had splicing changes that were outside the range of detection for the array (less than 2-fold). Two additional genes (MBP
) had a p
-value < 0.05 that were concordant with in silico
determined genes, but could not be validated by RT-PCR (Figure ). Finally, the lack of complete agreement in all of these gene lists could be due to the overall low level of aberrant splicing in GBM.
Many studies have shown that overexpression of a single cancer-enhancing isoform is sufficient to alter glioma cell proliferation or invasion [43
]. What remains unclear is how these specific isoforms are produced. Many cancers have over- or under-expression of splicing factors, which suggests that global aberrant splice events are possible. However, our analysis revealed that aberrant splicing factor expression does not lead to either large changes in specific exon utilization or widespread changes in the splicing of multiple targets. It is likely that titration of levels of multiple splicing factors is required to "fine tune" splicing decisions.