MB CISs define a network involved in neuronal development and human disease
5.2.7 Microarray expression analysis of mutagenized tumours identifies Igf2 as a key network-associated gene
Having established that the tumours generated by SB mutagenesis of Ptch1+/- mice are representative of the human MB SHH subgroup tumours, the next question was what impact disruption of the expression network by SB insertion in one or more network CIS gene had upon gene expression. Hence, the mouse expression data were split into network-hit and non-network-hit samples. Very few significantly differentially expressed genes were defined by this approach, with the top genes shown in Table 5.3. Igf2 was the highest differentially expressed gene with a mean fold change of 3.58 (p=0.002). This suggests that the network activity may have an effect on some aspects of the insulin-signalling pathway.
To validate the relationship between the activity of the CISs within the network and Igf2 expression, a quantitative RNA expression analysis using TaqMan real-time
Figure 5.8: SB induced murine and Ptch+/- MBs are SHH subgroup tumours. Projection
of four sub-group specific metagenes derived from 108 human primary MB expression profiles (Training Set) onto MB mouse model expression profiles (Test Set) using Non- negative Matrix Factorisation (NMF). A. Heatmaps depicting expression of metagenes within human cancers (training; left panel) and expression of metagenes throughout murine
tumours (test; right panel). B. Pseudo-plot of NMF projections coloured according to confident MB sub-group classifications by Support Vector Machine trained on human primary medulloblastoma using metagene expression values. This unsupervised analysis shows that the majority of Ptch mouse model samples recapitulate the expression profiles of
PCR was carried out to confirm and quantify the expression of Igf2 in all available MB mouse tumours used for the insertion site analysis, compared with the normal cerebellum.
Illumina
Probe_ID Gene Name
Mean Fold Change in Expression: Network vs. non-Network P-value LMN_2597769 Igf2 3.58 0.002 ILMN_1255871 Loxl1 1.64 0.029 ILMN_2757232 Aqp4 1.64 0.037 ILMN_1242456 Kank1 0.66 0.002 ILMN_2642012 LOC100046457 0.65 0.007 ILMN_2731265 Hsd11b2 0.65 0.026 ILMN_1252076 Lyz2 0.64 0.040 ILMN_1230157 Rnd3 0.61 0.038
The expression of Igf2 was analysed in tumours with hits in the network and those without. Confirming the Illumina bead array result, a significantly higher expression of Igf2 was detected in tumours with inserts in the network than in tumours without a network hit (p=5.2 E-06, Figure 5.9A). Moreover, Igf2 expression was significantly higher in tumours with hits in Nfia, the most frequently inserted CIS gene, than tumours with no inserts in the Nfia gene (p=0.018, Figure 5.9B). It is also noteworthy that Igf2 was expressed at a very high level within some network tumours, when compared to expression in the normal cerebella, with expression in some non-
Table 5.3: Gene expression difference between tumours with and without network hits.
Figure 5.9: Relative Igf2 expression in network and Nfia inserted tumours. A.
Box and whisker plots showing Igf2 expression in tumours with inserts in 1 or more network CIS versus tumours with no inserts. B. Igf2 expression in tumours with 1 or more insertions in Nfia, versus tumours with no Nfia insert but with inserts in at least 1
other network CIS gene. Boxes represent the 25th to 75th percentile, with median values shown as solid lines. Whiskers represent 95th percentile, and outliers are shown
individually. C. Relative Igf2 expression in murine tumours and cerebellum. Relative gene expression is shown, calculated using the 2-ΔΔCt method, using the
5.3 Discussion
Gene expression data sets obtained both from publicly available sources, and generated de novo from murine tumours generated during the SB screen, have been used here to investigate the possibility of interactions between CIS genes, and to check the appropriateness of the Ptch1+/- model for comparative studies. Reassuringly, the results confirm that the tumours induced by whole-body SB mutagenesis most closely resemble human SHH subgroup tumours in terms of gene expression patterns. This is clearly seen through the NMF and SVM results (Figure 5.8 A and B). All SB induced murine tumours and Ptch1+/- tumours clustered with human SHH subgroup tumours.
The network and gene ontology analysis used here provides a more in-depth look at how the CISs identified in the SB screen may interact with each other, and implies a role for the network in both neuronal development and cancer formation. The ARACNe analysis suggests that at least 7 CIS genes identified in this study are linked to each other within a single transcription factor network which does not map directly to a known signalling pathway. Interestingly, four out of the seven MB CIS genes that defined the network, namely CREBBP, NF1A, NFIB and TEAD1, as well as three other genes within the network (ERBB4, DIP2C and EDIL3), have been identified as MB CISs in a recent tissue specific SB mutagenesis screen of primary tumours within the Ptch1 model (Wu et al., 2012) shown as diamonds in Figure 5.2). It is also noteworthy that MYT1L is the most highly-networked gene among the CISs, indicative of an important role as a key co-ordinator. Furthermore, expression of MYT1L impacts upon survival.
The gene ontology results suggest that the normal biological impact of these CISs in the cerebellum is integrated toward a single output, neuronal differentiation/development, and that perturbation of this network (through SB mutation in mouse or expression changes in human) enhances tumour formation.
The significant enrichment for genes critical for neuronal architecture within the network is of particular interest, and many individual genes have important known neuronal functions. For example, one of these genes, Pclo (Presynaptic cytomatrix protein), is involved in synaptic formation where it can negatively regulate synaptic
cells, such as neuronal cells, toward apoptosis (Klumpp et al., 2006) suggesting its role in cancer formation needs to be assessed further. From the network analysis, this gene may be a target of Tgif2 and Myt1l. Dendrite microtubule-associated protein MAP2 is a large neuronal protein expressed predominantly within dendrites of mammalian brain tissues. It is considered a neuronal marker as it is involved in the microtubule-associated complex that is necessary for neurogenesis (Johnson and Jope, 1992;Sanchez et al., 2000;Suzuki et al., 2011). Another important networked gene involved in regulating neuronal activities is Gamma-aminobutyric acid B receptor (GABBR2). This gene is highly expressed in the dendrites of Purkinje cells (Chung et al., 2008a). It has an inhibitive neurotransmitter effect in the central nervous system. It is believed that the dysfunction of this gene governs a variety of nervous system disorders. For example, hypoactivity of this gene is associated with schizophrenia and bipolar disorder, based on analysis of post-mortem samples (Fatemi et al., 2011). Furthermore, GPHN is a cornerstone of the inhibitory process of neurotransmitter receptors to the microtubule matrix of the postsynaptic cytoskeleton. This process is performed via highly active binding to a tubulin dimer and inhibitory glycine receptor (Gly R) domain. Missense and deletion mutations of this gene may cause hyperekplexia and MoCo deficiency-like symptoms, respectively (Reiss et al., 2001;Rees et al., 2003). Both disorders display severe and fatal neurological damage.
All of these genes are involved in processes, or structures, associated with differenting/differentiated neurons, and are expressed at a lower level in SHH subgroup tumours than group 3 and 4 tumours. This is consistent with a block/downregulation of expression by the SB mutations within the linked CIS genes, leading to maintenance of an immature cellular phenotype, diverting the normal direction of neuronal cells from the differentiation process toward proliferation. Also, from the function of the genes it could be inferred that the mutation of the network TF CISs work synergistically with the disrupted SHH signalling pathway in the mouse model to maintain undifferentiated, highly proliferative cells, one of the known hallmarks of tumourgenesis.
One of the key observations from this analysis is that the mutated CISs identified here appear to synergise to increase the expression of Igf2 – a key gene already known to be critical for medulloblastoma development in the Ptch1+/- mouse model. The higher expression of Igf2 within SB induced tumours with insertion in the network reported here provides further evidence for the importance of Igf2 in terms of MB generation, and potentially identifies key genes involved in regulating the expression of this gene in developing cerebellar GNPCs.
The first clear indication for Igf2 involvement in MB was a study conducted by Hahn et al., 2000, which aimed to assess the impact of Igf2 upon MB and rhabdomyosarcoma (RMS) tumourgenesis. The Igf2 gene is imprinted with only the paternal allele being expressed and they found that Igf2 was upregulated in Ptch1+/- RMSs due to high expression of the imprinted allele driven by one alternative promoter (P3). To assess the impact of Igf2 upon MB and RMS formation, the murine Ptch1+/- allele used here was transferred into an Igf2 null background. This resulted in the frequency of tumour formation dropping to almost zero, indicating that Igf2 expression is essential for tumour formation. Furthermore, loss of the Ptch1 wild type allele from embryonic tissue was accompanied by increased Igf2 expression, suggesting that the gene may also be a target of the Shh signalling pathway.
Subsequently, Rao et al., 2004, used cell-type specific postnatal gene transfer to express Igf2 and Shh alone and in combination in cerebellar granule neuron precursor cells (GNPCs), to investigate the roles of Igf2 and Shh in MB formation. Transfection of Igf2 alone resulted in no tumour generation. However, co-transfection of Igf2 with Shh increased the frequency of tumours relative to Shh alone from 15% to 39%. Immunohistochemical analysis of Igf2/Shh tumours established that they were classical MBs expressing neural progenitor/early differentiation markers (β-III Tubulin and Neu N), but not markers of terminal differentiation such as glial fibrillar acidic protein (GFAP) and neurofilament protein. Immunoperoxide staining using antibodies against components of the Igf2 signalling pathway (Igf1R, IRS-1, AKt) establishing that Igf2 signalling was activated in MBs generated by both Shh only and through the combination of Igf2 and Shh.
Recently, Igf signalling pathways were assessed in terms of their synergistic action with Shh induced proliferative cells. Immunocytochemistry was used to establish the precise location of Igf signalling elements in the developing mouse cerebellum (Fernandez et al., 2010). Igfr1 (the main Igf receptor) was observed to be expressed ubiquitously at all stages and very strongly in the external granule layer (EGL). Igf1 was expressed in Purkinje neurons from E17.5, but not uniformly, and peaked at postnatal day 5 (P5). In contrast, the expression of Igf2 was specific to the meninges overlaying
incorporation. As expected, all showed mitogenic effects, with SHH being most strong. Synergy was clear as Shh plus either Igf increased BrdU incorporation ~3X relative to Shh only, and ~7X relative to either Igf. Inhibition of smoothened (SMO) using cyclopamine drastically reduced the impact of Shh, but had no effect upon Igf induced proliferation. Antagonism of Igfr1 with a blocking antibody effectively blocked the response in Igf treated cells, while Shh induced proliferation was inhibited by >50% by blocking Igfr1 as well. Furthermore, while Igfbp2, 3 and 5 were all able to inhibit the impact of Igf upon proliferation, Igfbp5 was also able to inhibit the impact of Shh. Collectively, these findings illustrate the significant synergistic impact of Igfs upon Shh induced proliferation, and also indicate that Igfbps can modulate both signalling networks in a complex manner (Fernandez et al., 2010).
It is also noteworthy that several of the CIS genes identified by the SB screen have already been implicated in Igf2 regulation. For instance, in prostate cancer Igf2 expression is elevated due to the EGR1 gene, a gene that is co-activated by CREBBP, one of our network CIS genes (Svaren et al., 2000;Yu et al., 2004;Lai and Wade, 2011). Furthermore, the expression of IGF2 is downregulated by the increased expression of PTEN in hepatoma tumours (Kang-Park et al., 2003): We would therefore predict Igf2 expression to be induced by PTEN loss of function, the inferred impact of SB insertion observed here. Collectively, the high Igf2 expression in murine tumours with network hits, the evidence that specific network CIS play an role in Igf2 expression, and the proven synergy between Shh and Igf2 in tumour development, provide strong evidence that the network identified here underpins Igf2 upregulation, critical for MB progression.
An obvious question which remains unanswered by this analysis is why, if the Ptch1+/- model accurately mimics gene expression in human SHH subgroup tumours, has Igf2 not been identified as a key SHH upregulated gene in any human microarray study to date. The Affymetrix probes for Igf2 on human microarray chips are known to have low specificity due, at least in part, to the existence of readthrough transcripts from an upstream gene (INS). For example probesets 202409_at, 202410_x_at and 210881_s, which are on the U133 Plus 2 chip, hybridise to a minimum of 2 genes, raising the possibility that Igf2 expression is not accurately assayed. This is supported by recent analyses by collaborators in Newcastle using RNAseq which have established that increased Igf2 expression is one of the strongest SHH specific expression signals (S. Clifford and D. Williamson, personal communication). More importantly, this accounts for an apparent anomaly between the human and mouse datasets analysed here, and
further supports the conclusion that the transcription factor network defined here undperpins Igf2 upregulation and MB progression in both mouse and human. This suggests that further analysis of the genes identified, and the processes they affect, may identify valid targets for novel therapeutic strategies. It is the prioritisation of these genes for further study, and their preliminary analysis, which is the subject of the final results chapter.