1. Human Biology and Medicine
  2. Neuroscience
Download icon

Mouse models of human PIK3CA-related brain overgrowth have acutely treatable epilepsy

  1. Achira Roy
  2. Jonathan Skibo
  3. Franck Kalume
  4. Jing Ni
  5. Sherri Rankin
  6. Yiling Lu
  7. William B Dobyns
  8. Gordon B Mills
  9. Jean J Zhao
  10. Suzanne J Baker
  11. Kathleen J Millen  Is a corresponding author
  1. Seattle Children's Research Institute, United States
  2. Dana Farber Cancer Institute, United States
  3. St. Jude Children's Research Hospital, United States
  4. The University of Texas MD Anderson Cancer Center, United States
Research Article
  • Cited 8
  • Views 1,910
  • Annotations
Cite as: eLife 2015;4:e12703 doi: 10.7554/eLife.12703

Abstract

Mutations in the catalytic subunit of phosphoinositide 3-kinase (PIK3CA) and other PI3K-AKT pathway components have been associated with cancer and a wide spectrum of brain and body overgrowth. In the brain, the phenotypic spectrum of PIK3CA-related segmental overgrowth includes bilateral dysplastic megalencephaly, hemimegalencephaly and focal cortical dysplasia, the most common cause of intractable pediatric epilepsy. We generated mouse models expressing the most common activating Pik3ca mutations (H1047R and E545K) in developing neural progenitors. These accurately recapitulate all the key human pathological features including brain enlargement, cortical malformation, hydrocephalus and epilepsy, with phenotypic severity dependent on the mutant allele and its time of activation. Underlying mechanisms include increased proliferation, cell size and altered white matter. Notably, we demonstrate that acute 1 hr-suppression of PI3K signaling despite the ongoing presence of dysplasia has dramatic anti-epileptic benefit. Thus PI3K inhibitors offer a promising new avenue for effective anti-epileptic therapy for intractable pediatric epilepsy patients.

https://doi.org/10.7554/eLife.12703.001

eLife digest

An enzyme called PI3K is involved in a major signaling pathway that controls cell growth. Mutations in this pathway have devastating consequences. When such mutations happen in adults, they can lead to cancer. Mutations that occur in embryos can cause major developmental birth defects, including abnormally large brains. After birth, these developmental problems can cause intellectual disabilities, autism and epilepsy. Children with this kind of epilepsy often do not respond to currently available seizure medications.

There are several outstanding questions that if answered could help efforts to develop treatments for children with brain growth disorders. Firstly, how do the developmental abnormalities happen? Do the abnormalities themselves cause epilepsy? And can drugs that target this pathway, and are already in clinical trials for cancer, control seizures?

Now, Roy et al. have made mouse models of these human developmental brain disorders and used them to answer these questions. The mice were genetically engineered to have various mutations in the gene that encodes the catalytic subunit of the PI3K enzyme. The mutations were the same as those found in people with brain overgrowth disorders, and were activated only in the developing brain of the mice. These mutations caused enlarged brain size, fluid accumulation in the brain, brain malformations and epilepsy in developing mice – thus mimicking the human birth defects. The severity of these symptoms depended on the specific mutation and when the mutant genes were turned on during development.

Next, Roy et al. studied these mice to see if the seizures could be treated using a drug, that has already been developed for brain cancer. This drug specifically targets and reduces the activity of PI3K. Adult mutant mice with brain malformations were treated for just one hour; this dramatically reduced their seizures. These experiments prove that seizures associated with this kind of brain overgrowth disorder are driven by ongoing abnormal PI3K activity and can be treated even when underlying brain abnormalities persist. Roy et al. suggest that drugs targeting PI3K might help treat seizures in children with these brain overgrowth disorders.

https://doi.org/10.7554/eLife.12703.002

Introduction

The phosphoinositide-3 kinase (PI3K)-AKT pathway is a central player of intracellular signaling, conserved from yeast to mammals. Activating mutations in genes of PI3K-AKT signaling pathway, especially PIK3CA, encoding the catalytic p110α isoform of the PI3K complex, have long been linked to cancer (Cheung and Testa, 2013; Engelman, 2009; Hennessy et al., 2005; Iwabuchi et al., 1995; Samuels and Waldman, 2011; Gymnopoulos et al., 2007). Germline and mosaic mutations of PIK3CA and other pathway genes also cause a wide range of brain and body overgrowth disorders; all anomalies caused by somatic PIK3CA mutations are now collectively termed PIK3CA-Related Overgrowth Spectrum (PROS) (Keppler-Noreuil et al., 2014). The broad spectrum of brain overgrowth disorders caused by PIK3CA activating mutations is impressive. Three strongly activating PIK3CA mutations found most commonly in cancer (hotspot mutations) result in severe segmental cortical dysplasia (SEGCD), which includes bilateral dysplastic megalencephaly (MEG), hemimegalencephaly (HMEG) and focal cortical dysplasia (FCD) types 2a/2b (Lee et al., 2012; D'Gama et al., 2015; Conway et al., 2007; Jansen et al., 2015). Other mutations, resulting in intermediate or weak PIK3CA activation, cause MEG or MEG with polymicrogyria (MEG-PMG) as part of the MEG-capillary malformation syndrome (MCAP) (Conway et al., 2007; Mirzaa et al., 2012; Rivière et al., 2012). Developmental features of these brain disorders include cortical malformations, hydrocephalus, Chiari malformation, intellectual disability, autism and epilepsy (Keppler-Noreuil et al., 2014; Mirzaa et al., 2012). FCD represents one of the most common causes of intractable epilepsy (Bast et al., 2006; Fauser et al., 2015; Fauser, 2006).

Conditional mouse alleles for the H1047R and E545K Pik3ca hotspot mutations have been generated to study tumor formation and assess anti-cancer activities of pathway inhibitors (Kinross et al., 2012; Liu et al., 2011; Meyer et al., 2011; Robinson et al., 2012; Yuan et al., 2013). To understand the cellular mechanisms behind PIK3CA-related brain overgrowth disorders, we used a series of cre-drivers to activate expression of H1047R and E545K alleles in subsets of neural progenitors. Dramatic phenotypes resulted, faithfully modeling the entire spectrum of PIK3CA-associated human brain disorders including enlarged brain size, hydrocephalus, cortical dysplasia and epilepsy. The severity of these brain phenotypes critically depended on the Pik3ca allele and its time of activation. Notably, Pik3ca-associated epilepsy in mice was independent of brain overgrowth and cortical dysplasia. Further the seizures of adult megalencephalic mice were suppressed by acute 1 hr-administration of pan-PI3K inhibitor BKM120 (Maira et al., 2012). We conclude that epilepsy in these models represents an active Pik3ca-driven process that can be restricted by dynamic modulation of PI3K pathway activity in dysmorphic brains. These results raise the exciting prospect of new molecular based epilepsy therapies in patients whose seizures have been intractable to current anti-seizure therapies.

Results

Megalencephaly caused by Pik3ca overactivation is dependent on both the nature of the mutant allele and its time of overactivation

Two conditional Pik3ca activating alleles (H1047R and E545K) were crossed with cre-drivers to overactivate p110α in progressively restricted sets of neural progenitors and their progeny. The broadest distribution was achieved with Nestin-cre, being expressed in nearly all neural progenitors from early embryonic stages. A subset of late embryonic progenitors was targeted by hGFAP-cre; while tamoxifen-inducible Nestin-creER line drove cre-expression in a small subset of neural progenitors around birth. Expression of H1047R was dependent upon a tri-allelic system with tet-inducible mutant human cDNA activated by cre-dependent expression of the tet-activator protein (Liu et al., 2011) (Figure 1—figure supplement 1). The E545K mutation was knocked into the endogenous Pik3ca locus and a lox-stop-lox cassette introduced upstream of the initiation-coding exon, rendering the mutant allele cre-dependent (Robinson et al., 2012). The activity of all cre drivers was confirmed using reporter lines (Figure 1—figure supplement 2).

The most severe phenotype was achieved in hGFAP-cre;H1047R mutants, when doxycycline was administered from embryonic day (E)0.5. All mutants exhibited progressive hydrocephalus and died prior to weaning. Hydrocephalus was evident as a domed forehead at postnatal day (P)21 (Figure 1b). Hematoxylin-eosin stained P3 sections showed ventriculomegaly in the megalencephalic H1047R mutant brains. Strikingly the hippocampus was not evident in these mutants. Instead, the medial tissue was highly dysplastic with multiple infoldings along its entire length (Figure 1c,d). In contrast, when pups were treated with doxycycline from P1, no morphological differences were observed between the control and the hGFAP-cre;H1047R mutant (Figure 1—figure supplement 3). Thus the effect of H1047R mutation on brain size was dependent on time of activation.

Figure 1 with 3 supplements see all
Embryonic Pik3ca overactivation in mice causes MEG.

(a,b) Compared to control, P21 hGFAP-cre;H1047R mutants had domed foreheads. (c,d) Coronal section of H&E-stained P3 H1047R mutant showed bigger brain and enlarged lateral ventricles compared to control. Mutant neocortex (nctx) was dysplastic and medial tissue highly infolded (arrowhead; d). (e–g) P35 hGFAP-cre;E545K and Nestin-cre;E545K brains were noticeably larger than controls, while Nestin-creER;E545K mutants had normal-sized brains compared to controls. Red color of Nestin-creER;E545K brain is due to presence of a lox-stop-lox-Tomato reporter allele, and shows successful induction of cre activity. Controls for e,f and g are of genotypes Pik3ca E545K, hGFAP-cre, Nestin-cre and Nestin-creER. (h) MRI volumetric analyses of mutant and corresponding control brains. *p<0.0001; ns, not significant. Each data point in the graph represents 1 mouse. (i–l) Nissl-stained coronal sections of representative control and mutant brains. Scale bars: 1 mm (c,d); 2 mm (i-l). See also Figure 1—figure supplements 13.

https://doi.org/10.7554/eLife.12703.003

E545K mice with the same cre-driver (hGFAP-cre;E545K) had a milder phenotype, surviving as adults without hydrocephalus, though their brain size was significantly larger compared to control littermates (Figure 1e,h,j). This provides evidence that with identical time of activation by the same cre driver, the brain phenotypes are dependent on specific Pik3ca allele. Earlier activation of E545K mutation with Nestin-cre led to an even more striking 54.4% volumetric increase, with mild ventriculomegaly and no hydrocephalus (Figure 1f,h,k). Interestingly, neonatal activation of E545K using Nestin-creER had no apparent impact on brain size (Figure 1g,h,l). Enlarged head size in both Nestin-cre;E545K and hGFAP-cre;E545K mutants was evident at birth and brain size of all the three adult E545K mutants was relatively stable (data not shown). Unlike H1047R mutants, gross morphology was normal for all E545K mutants. We conclude that brain phenotypes caused by Pik3ca-overactivation are both allele and time dependent. Further, we conclude that to cause brain overgrowth, overactivation of Pik3ca function is required during embryogenesis.

Multiple allele-dependent embryonic mechanisms drive Pik3ca-MEG

To assess the mechanisms causing Pik3ca-dependent embryonic brain enlargement, we focused our analysis on hGFAP-cre;H1047R (doxycycline from E0.5) and Nestin-cre;E545K mutants, since these allelic combinations had the most extreme megalencephalic phenotypes.

The inner cortical length of hGFAP-cre;H1047R mutants was longer than controls at both E14.5 (p<0.01) and E16.5 (p<0.001; Figure 2b–g). This was accompanied by enlarged nuclear and cell size at both ages and decreased cell density at E16.5, but not increased proliferation or cell cycle exit (Figure 3c–l). Total cell number per cortical column length was not significantly different between control and H1047R mutant both at E14.5 and E16.5. Also, TUNEL+ cell number was significantly lower in E16.5 mutant cortex than in control (p<0.01), indicating reduced apoptosis (Figure 3—figure supplement 1a,c); however the overall TUNEL+ cell numbers for both control and mutant were small. Together these results indicate that cortical expansion in hGFAP-cre;H1047R mutant was not primarily driven by increased proliferation or reduced apoptosis; rather reduced cell density and increased cell size during embryogenesis were major contributing factors.

Pik3ca activating mutations lead to increased embryonic cortical length.

(a) Schematic shows how cortical length and thickness were measured. F, fimbria/cortical hem. Nissl-stained coronal sections of control (b,e,h,k) and mutant (c,f,I,l) brains. (b–g) Cortical length of hGFAP-cre;H1047R mutant at E14.5 and E16.5 was longer than control; cortical thickness was not different. (h–m) Cortical length of Nestin-cre;E545K mutant was longer than control at E16.5 but not at E14.5; thickness was not different at E14.5 but was smaller than control at E16.5. Data are represented as mean ± SEM. *p<0.05; **p<0.01; ***p<0.001. Scale bars: 300 μm (b,c,e,f,h,i,k,l).

https://doi.org/10.7554/eLife.12703.007

By contrast, in Nestin-cre;E545K mutants, the inner cortical length was comparable to controls at E14.5 but elongated at E16.5 (p<0.01); cortical thickness was slightly reduced in E16.5 (p<0.05) as compared to controls (Figure 2h–m). The labeling index was similar to the control at E14.5 but increased in E16.5 mutants (p<0.05), indicating more proliferation (Figure 3m,o,r). Cell density in E545K mutant neocortex was similar to the control at E14.5 but was reduced at E16.5 (p<0.05). Total cells per cortical column length did not change in the E545K mutant; but the TUNEL+ cell number was lower in E16.5 mutant cortex than in control (p<0.001). Intriguingly, the nuclear size of these mutant cells was similar to controls at both E14.5 and E16.5 but cell somas were significantly larger (p<0.05) at E16.5 (Figure 3n,p,q,s,t). The quit fraction indicative of rate of cells exiting cell cycle was significantly higher (p<0.05) in the E545K mutant between E15.5 and E16.5 (Figure 3u,v). At P35, the neocortical cells of Nestin-cre;E545K mutant were still larger (p<0.05) compared to controls (Figure 3—figure supplement 2a,b). Notably, in the adult P35 Nestin-creER;E545K mutant mice, where activation was initiated in neonates, and brain size was not different from controls, E545K-activated (YFP+) cells have the same size as controls (Figure 3—figure supplement 2c,d). We conclude that increased cell size due to E545K overactivation also has a critical embryonic period. Further, changes in multiple developmental parameters including proliferation, cell cycle exit, cell size and density contribute to MEG of Nestin-cre;E545K Pik3ca embryonic overactivation.

Figure 3 with 2 supplements see all
H1047R and E545K mutations differentially affect proliferation, cell density and size in neocortex.

(a) Schematic shows area of interest (red box) in E16.5 mouse coronal section, as depicted in c,d,k,m,n,u. (b) Experimental outline of the proliferation and cell cycle exit assays. For labeling index, E14.5 and E16.5 control and mutant brains, harvested after a 1hr BrdU pulse, were processed for BrdU and DAPI staining (c,m). For quit fraction analysis, E16.5 control and mutant brains, pulsed with BrdU at E15.5, were processed for BrdU and Ki67 (k,u). Magnified view of DAPI-stained cortical nuclei shows differences in size and density between controls and mutants (d,n). (e-j,l) E14.5 and E16.5 H1047R mutants had similar labeling indices (BrdU+ cells/total DAPI+ cells); E16.5 H1047R mutant neocortex displayed reduced cell density (x105 DAPI+ cells/mm3 volume), larger nuclear and cell size (μm2) and similar quit fraction (BrdU+Ki67- cells/total BrdUcells). (o-q) E14.5 E545K mutant neocortex was similar to control in labeling index, cell density and nuclear size. (r-t,v) E16.5 E545K mutant showed significantly higher labeling index and quit fraction, reduced cell density, and enlarged cell and nuclear size, compared to controls. Data are represented as mean ± SEM (e,f,h,i,I,o,p,r,s,v) or as median-centered box-and-whisker plots (g,j,q,t); *p<0.05; **p<0.001; ***p<0.0001. Scale bars: 50 μm (c,d,m,n); 100 μm (k,u). See also Figure 3—figure supplements 12.

https://doi.org/10.7554/eLife.12703.008

Embryonic Pik3ca activation results in cortical dysplasia

Since disordered lamination is a key feature of human SEGCD (Arai et al., 2012; Rossini et al., 2014), we assessed neocortical organization and development in both hGFAP-cre;H1047R and Nestin-cre;E545K mutants. First, we studied the effect of Pik3ca overactivation on the Nestin-positive radial glial fibers, the scaffold for glial-guided neuronal migration, at multiple developmental stages. In H1047R mutants, the radial glial scaffold was slightly fasciculated and irregular at E14.5 and E16.5. Irregularities were very prominent at P0 when a disrupted pial surface was associated with irregular clusters of enlarged radial glial end-feet (Figure 4—figure supplement 1). The radial glial phenotype was much more subtle in the E545K mutant at E14.5 and E16.5; however at P0, we observed thinning of radial glial fibers and irregular clusters of end-feet at the intact pial surface (Figure 5—figure supplement 1).

Cajal-Retzius cells expressing Reelin, a major regulator of radial migration, were normally present in an ordered array in the marginal zone (layer I) of controls and Nestin-cre;E545K mice (Figure 4b; Figure 5b,c). However, these cells were dysplastic in hGFAP-cre;H1047R mice at E16.5 (Figure 4c,c’). We did not observe ectopic Reelin-positive cells within the cortical column in either mutant. As expected, within the developing wildtype neocortex, Ctip2 and Tbr1 were expressed predominantly in the early-born, deep layers (layers V-VI), while Cux1 was expressed in late-born upper layers (layers II-IV). hGFAP-cre;H1047R mutants displayed a marked disorganization of all layers. Ctip2/Tbr1-positive as well as Cux1-positive cells in the E16.5 H1047R mutant were dispersed throughout the cortical plate, with both early- and late-born neurons severely mislocalized (Figure 4d–g). Laminar disorganization was less severe in E16.5 Nestin-cre;E545K brains, but deep Ctip2/Tbr1-positive neurons and upper Cux1-positive neurons were dispersed throughout the cortical plate (Figure 5f,g).

Figure 4 with 2 supplements see all
H1047R mutant mice display abnormal neocortical layering.

(a) Schematics of mouse brain and section; section corresponds to the marked coronal plane; red box in the section marks the area of neocortex (nctx) depicted in the images below. (bg) and (h–m) correspond to ages E16.5 and P3 respectively. In control cortex, Reelin is in layer I (b), Ctip2 and Tbr1 in deep layers VI and V (d,j), Cux1 in upper layers II-IV (f,l) and NeuN in all matured neurons (h). H1047R mutants displayed abnormal distribution of cells for all neocortical layers, observed at E16.5 and P3 (c,e,g,i,k,m). (b’,c’) Magnified view of Reelin-positive cells in control and H1047R mutant. P3 H1047R mutant showed enlarged area between ventricular zone (vz) and cortical plate and absence of clear subplate (sp) boundary (h-k). A, anterior; P, posterior; yellow dashed lines, lateral ventricular lining; white dotted lines, pial surface; I-VI, neocortical layers; arrowheads, mispositioned mutant cells. Scale bars: 25 μm (b’,c’), 50 μm (b-i), 150 μm (j-o). See also Figure 4—figure supplements 12.

https://doi.org/10.7554/eLife.12703.011
Figure 5 with 3 supplements see all
E545K mutant mice display abnormal neocortical upper layers.

(a) Schematics of mouse brain and section; section corresponds to the marked coronal plane; red box marks the area of neocortex (nctx) depicted in the images below. (b-g) and (h-m) correspond to ages E16.5 and P35 respectively. (b-g) Compared to control, in E16.5 E545K mutant, layer I appeared normal; deep layers lacked normal arrangement while Cux1-positive cells were dispersed throughout the cortical plate. Extent of dispersion was reduced postnatally (h-m). vz, ventricular zone; yellow dashed lines, lateral ventricular lining; white dotted lines, pial surface; I-VI, neocortical layers; arrowheads, mispositioned mutant cells. Scale bars: 50 μm (b-g), 150 μm (h-m). See also Figure 5—figure supplements 13.

https://doi.org/10.7554/eLife.12703.014

Laminar patterns in postnatal animals remained disrupted in both mutants, with hGFAP-cre;H1047R cortex more affected Nestin-cre;E545K mutant cortex (Figure 5h–m). Thus a simple developmental delay was not the cause of dysplasia (Figure 4h–m; Figure 5h–m). In P3 hGFAP-cre;H1047R mutants, NeuN-positive mature cortical neurons were found within the normally cell-sparse marginal zone as well as in the cortical white matter and residual ventricular zone, a feature reported in SEGCD patients (Arai et al., 2012). Further, the cortical subplate was not readily discernible in these mutants (Figure 4h–k; Figure 4—figure supplement 2e,f), blurring the boundary between grey and white matter – a feature often observed in SEGCD patients (Rossini et al., 2014).

To determine whether the mislocalization of neocortical cells was due to defects in cell fate specification and/or migration, we labeled cells at either E12.5 or at E16.5 with pulse of BrdU and assessed cortical neuronal location and fate (layer V; Ctip2+ and layers II/III; Cux1+) (Figure 6a). The total numbers of BrdU+ P0 cells, born at E12.5 and E16.5, were not significantly different between controls and either hGFAP-cre;H1047R or Nestin-cre;E545K mutants (Figure 6b,j). The distribution of BrdU+ cells showed significant differences between controls and H1047R mutants labelled during both early and late embryonic stages. At P0, more BrdU+ cells were localized in the lower cortical plate (CP) and white matter (Figure 6c). For E545K mutants the BrdU+ cell numbers were not different at either age. The distribution was subtly, yet significantly different only for the early born neurons (Figure 6k). For both the H1047R and E545K Pik3ca activating alleles, total layer V (Ctip2+) cell numbers at P0 were not significantly different between controls and mutants (Figure 6d,l). Also, the numbers of Ctip2/BrdU double-labeled cells were the same in controls and mutants, indicating that cell fate specification for these deep layer neurons was unaffected by either the H1047R or E545K Pik3ca allele (Figure 6e,m). However, similar to the overall BrdU+ cell distribution, the specific distribution of layer V neurons was abnormal in H1047R mutants, with ectopic Ctip2/BrdU double-labeled cells in the upper and lower CP and white matter, instead of mid CP (Figure 6f). In E545K mutants, fewer Ctip2+ cells were positioned in the mid CP (Figure 6n), although the phenotype was much less severe.

Birthdating assays demonstrate defects in laminar distribution.

(a) Experimental outline of birthdating assays: BrdU was injected at E12.5 and E16.5 and analyzed at P0 (B12.5;P0 and B16.5;P0). Total number of BrdU+ cells at P0 generated at E12.5 and E16.5 (b,j), and total number of Ctip2+ cells (layer V neurons; d,l) were not significantly different between respective controls and mutants, for both H1047R and E545K lines. (c) Distribution of BrdU+ cells in the neocortex was significantly different between control and hGFAP-cre;H1047R mutant for both early and late assays, with more cells residing in the lower cortical plate and white matter instead of mid and upper zones of the cortical plate. (e,m) Total number of layer V neurons in both H1047R and E545K mutants, born at E12.5 and at E16.5, did not significantly differ from the respective controls; but showed significant difference in their zonal distribution with Ctip2+BrdU+ cells predominating the lower cortical plate in both the mutants (f,n). Total number of Cux1neurons (layers II/III neurons; g,o) was significantly higher in both the mutants compared with the respective controls. The colocalization of Cux1 and BrdU was not significantly different in the H1047R mutant and control for both ages (h); but number of Cux1+ cells born at E16.5 was significantly higher in E545K mutant than in the control (p). (i,q) Zonal distribution of Cux1+ cells was significantly different between controls and mutants, with more Cux1+ cells residing at the lower portion of the P0 cortical plate. The H1047R mutant phenotype is more extreme than the E545K mutant. Data are represented as mean ± SEM. *p<0.05; **p<0.001; ***p<0.0001.

https://doi.org/10.7554/eLife.12703.018

Upper layer (Cux1+) neuronal numbers and distributions were significantly different in both H1047R and E545K mutants, compared to their respective controls (Figure 6g,o). In E545K mutants, the increase in total Cux1+ cell numbers in the E545K mutant corresponded to increased Cux1/BrdU double-labeled cells, born at E16.5 (Figure 6p). However, no such correlation was observed in E12.5 or E16.5-born Cux1+ cells in the H1047R mutant (Figure 6h). These extra cells were therefore likely born between E16.5 and P0. The distribution of Cux1+ cells was disrupted in both mutants, with the H1047R mutant displaying the more severe phenotype (Figure 6i,q). Together, these data indicate that cell fates are largely correctly specified in both Pik3ca mutants and that cortical dysplasia is more likely caused by aberrant neuronal migration.

Pik3ca mutations cause white matter dysplasia

In P3 hGFAP-cre;H1047R mutants, although the cortical plate itself was not dramatically thicker than controls, the underlying cortical white matter was much thicker (Figure 4j,k; Figure 4—figure suplement 2e,f). This was less pronounced but readily discernible in P3 Nestin-cre;E545K mutants (Figure 5—figure supplement 2c,d). In P3 H1047R mutants, there was complete absence of corpus callosum, although hippocampal and anterior commissures were present (Figure 4—figure supplement 1a-d). In contrast, all major tracts were present in P3 E545K mutants (Figure 5—figure supplement 2). These data are consistent with the wide spectrum of white matter dysplasia reported in MEG and SEGCD patients (Conway et al., 2007; Adamsbaum et al., 1998; De Rosa et al., 1992; Jansen et al., 2015). Moreover, increased number of Olig2-positive cells was observed in the white matter area of both H1047R and E545K mutants (Figure 4—figure supplement 2, Figure 5—figure supplement 2). Although astrocytosis is observed when mTOR signaling is activated by TSC mutations in humans and mice (Sosunov et al., 2008; Zeng et al., 2008), it is not a feature of PIK3CA-pathology in our mouse models (Figure 5—figure supplement 3a-d).

Both megalecephalic and normocephalic E545K mutant mice are epileptic

Epilepsy is one of the most important clinical features of SEGCD (Bast et al., 2006; Fauser et al., 2015; Fauser, 2006; Arai et al., 2012). Since most of the H1047R mutants were not viable post-weaning, we assessed Nestin-cre;E545K (megalencephalic) and Nestin-creER;E545K (normocephalic) adults for epilepsy phenotypes. Baseline sleep EEG recordings in both animal models revealed epileptiform activity including sets of spikes/polyspikes, and regional and generalized spike and wave discharges during non-rapid eye movement (NREM) sleep (Figure 7b,c). We also conducted additional 2 hr of continuous EEG recording immediately after 5 hr of total sleep deprivation of the Nestin-creER;E545K mice. Sleep deprivation is commonly implemented during epilepsy diagnostic studies in mice and humans and increases the sensitivity and specificity of EEG diagnosis for epilepsy (De Rosa et al., 1992; Giorgi et al., 2013; Binnie and Prior, 1994; Kalume et al., 2015). The frequency of epileptiform interictal activity was increased in post sleep deprivation EEG recordings, and clinically relevant spontaneous seizures including myoclonic (MC) seizures, frequent isolated spikes, and train of spikes, were observed in the Nestin-creER;E545K mice (Figure 7d,e).

Figure 7 with 1 supplement see all
PI3K activity acutely modulates epileptic seizures.

(a) Schematic shows electrode placement for EEG recordings. LF=Left Frontal, LP= Left Posterior, RF=Right Frontal, RP= Right Posterior. Only 2 electrodes were placed in P35 Nestin-cre;E545K. (b) EEG-EMG tracings of Nestin-cre;E545K mutant showed bilateral spikes/polyspikes, myoclonic (MC) seizures, fast and slow wave discharges, not associated with movement on video or EMG activity. (c) Generalized (G) and regional (R) spike and wave discharges were observed in Nestin-creER;E545K mice. Scale: 1s,1mV. (d,e) Sleep deprivation (SD) enhances epileptiform EEG activity in Nestin-creER;E545K mutant. EEG tracings of a Nestin-creER;E545K mutant mouse after 5 hr of normal sleep (Pre SD) and after 5 hr of total sleep deprivation (Post SD) in the same mouse (d), the mutant showing myoclonic (MC) seizures and isolated regional spikes (R). Power spectrum analysis, representing the frequency distribution for EEG activity over time, also displayed increased activity of the mutant post SD (e). (f) Bar chart showing average number of seizures (SZ) in PTZ-induced P35 Nestin-cre;E545K and control over time. (g) Experimental outline for BKM120-PTZ test. (h) Total number of seizures was significantly higher in P35 mutants than controls. Acute administration of BKM120 reduced number of seizures in mutants. (i) Duration of sustained generalized tonic-clonic seizure state (Racine 5), normalized to the total time of test, was significantly longer in P35 Nestin-cre;E545K mutants than controls. BKM120 significantly reduced the duration. Data are represented as mean ± SEM. *p<0.05; **p<0.0001. See also Figure 7—figure supplement 1.

https://doi.org/10.7554/eLife.12703.019

When challenged with the chemoconvulsant pentylenetetrazol (PTZ), a GABA-A receptor antagonist (Macdonald and Barker, 1978), both the megalencephalic and normocephalic E545K mouse models exhibited lower seizure thresholds compared to controls at both P35 and P180 (Figure 7f–i; Figure 7—figure supplement 1d). In the 30 min post PTZ injection, both models showed shorter latencies to first generalized tonic clonic (GTC) seizures, more myoclonic seizures, and a prolonged seizure load.

We conclude that Pik3ca overactivation is sufficient to cause epilepsy. Further our data indicate that Pik3ca-related epilepsy is dissociable from brain overgrowth and cortical dysplasia.

Acute inhibition of Pik3ca activity suppresses epilepsy, rapidly altering cell signaling

BKM120, a 2,6-dimorpholino pyrimidine derivative, is an orally available pan-Class I PI3K inhibitor currently in clinical trials for solid tumors (Maira et al., 2012; Bendell et al., 2012; Brachmann et al., 2012) and may represent a novel therapeutic agent for PIK3CA-related epilepsy. Preclinical studies show that BKM120 maximally inhibits downstream phosphorylation of Akt, 1hr post-administration (Maira et al., 2012). To test its anti-seizure effects in our adult Pik3caE545K gain-of-function megalencephalic and normocephalic models, we administered 50 mg/kg BKM120 (Maira et al., 2012) by oral gavage 1hr prior to PTZ-challenge at ~P35. BKM120 increased the seizure threshold of control animals. More importantly, despite the presence of megalencephaly and considerable cortical dysplasia in P35 Nestin-cre;E545K megencephalic animals, BKM120 dramatically decreased the seizure number and duration to untreated control levels and marginally increased seizure latency in the mutant mice (Figure 7h,i; Figure 7—figure supplement 1d). These data powerfully demonstrate that dynamic Pik3ca-dependent processes, independent of cortical and cellular dysplasia, cause Pik3ca-related epilepsy and they are highly amenable to therapeutic intervention.

To begin to dissect the cell signaling mechanisms underlying Pik3ca-driven epilepsy, we conducted reverse phase protein array (RPPA) analysis to measure protein levels of a comprehensive panel of cell signaling molecules (Tibes et al., 2006). We assessed subdissected cortical and hippocampal tissue from untreated (-) and PTZ, BKM120 and BKM120 PTZ treated adult control and Nestin-cre;E545K mutants (Figure 8, Figure 8—figure supplement 1). As expected, untreated Nestin-cre;E545K mutants exhibited significant elevations of phospho (p)S473-Akt and pT346-NDRG1, consistent with PI3K pathway activation. Notably, baseline pS473-Akt levels in the Nestin-cre;E545K hippocampus were prominently higher than the cortical levels. In both E545K mutant and control brain tissues, PTZ treatment alone increased the levels of pAkt, especially pS473-Akt, of pS6 (pS235/S236, pS240/244), pT346-NDRG1 and pS2448-mTOR. As expected, acute BKM120 treatment alone reduced phosphorylation of multiple PI3K pathway members, including AKT, S6, NDRG1, GSK3 and 4EBP1. Most remarkably, BKM120 also inhibited the increased phosphorylation levels induced by PTZ, notably returning mutant hippocampal pS473-AKT levels to baseline untreated control levels.

Figure 8 with 1 supplement see all
BKM120 acutely alter PI3K pathway protein profile.

(a–g) Graphs show differential protein levels in P35 Nestin-cre;E545K mutant and control brains due to different treatments: untreated (-); BKM120; PTZ; BKM120+PTZ. Data are represented as mean ± SEM. *p<0.05. Inset shows simplified PI3K pathway; BKM120 significantly regulated the highlighted molecules. See also Figure 8—figure supplement 1.

https://doi.org/10.7554/eLife.12703.021

Discussion

PIK3CA-related disorders (PROS) in humans

Activating PIK3CA mutations have been associated with many human overgrowth disorders categorized based on severity and distribution of the mutation. Involvement of multiple tissues results in CLOVES or Klippel-Trenaunay syndrome with highly mosaic mutation levels (0.8–32%) in affected tissues (Luks et al., 2015; Kurek et al., 2012). Involvement of single tissue or body segment results in epidermal nevi, lymphatic malformations or other localized phenotypes with usually no mutations detected in unaffected tissues (Keppler-Noreuil et al., 2014; Luks et al., 2015; Kurek et al., 2012; Osborn et al., 2015; Groesser et al., 2012; Lindhurst et al., 2012; Hafner et al., 2007; Rios et al., 2013; Cohen et al., 2014). Too few patients and insufficient quantitative data have been reported to observe allele-specific differences.

In the brain, mosaic hotspot mutations result in SEGCD, classified as dysplastic MEG, HMEG or FCD2a based on extent of lesion (Jansen et al., 2015). PIK3CA mutations were detected in 9/73 patients with HMEG and 1/33 with FCD2 (Lee et al., 2012; D'Gama et al., 2015; Jansen et al., 2015). These overlapping SEGCD are associated with severe and usually intractable epilepsy (Bast et al., 2006; Fauser et al., 2015; Fauser, 2006; Pasquier et al., 2002; Russo et al., 2003; Tassi, 2002; Devlin, 2003; Blümcke et al., 2011). ~20 other PIK3CA mutant alleles have been seen in MCAP, characterized by MEG or MEG-PMG, hydrocephalus and less severe epilepsy (Gymnopoulos et al., 2007; Mirzaa et al., 2012; Rivière et al., 2012; Tatton-Brown and Weksberg, 2013).

We activated the two most common hotspot mutations, E545K and H1047R, in mouse brain at different developmental timepoints to generate the first models of human PIK3CA-related SEGCD. Our mouse models faithfully recapitulated the most important PIK3CA-related phenotypes of MEG, hydrocephalus, cortical and white matter dysplasia, and epilepsy (Table 1).

Table 1

Table displays comparison of the key features across different Pik3ca genetic models used in this study.

https://doi.org/10.7554/eLife.12703.023

Mutant allele

H1047R

E545K

Cre driver

hGFAP-cre(dox from E0.5)

hGFAP-cre(dox from P1)

Nestin-cre

hGFAP-cre

Nestin-creERT2(tamoxifen @P0/P1)

GoF expression onset

Late embryonic

Neonatal

Early embryonic

Late embryonic

Neonatal

Viability

Lethal by weaning age

Viable

Viable

Viable

Viable

Megalencephaly

X

✓ (intermediate)

X

Hydrocephalus

X

X

X

X

Increased cell size

Not tested

X

X

Cortical dysplasia

X

X

X

White matter dysplasia

X

✓ (data not shown)

X

Epilepsy

Not tested

Not tested

Not tested

Differential activating mechanisms underlie Pik3ca allele-specific brain phenotypes

Data from cancer biology suggests that H1047R mutation is more severe than E545K mutation. For example, E545K mutation accounts for 1932/7548 (26%) and H1047R for 2898/7548 (38%) of PIK3CA-coding mutations detected in the COSMIC database of cancer mutations (http://cancer.sanger.ac.uk/cancergenome/projects/cosmic).

We found that H1047R and E545K mutations caused distinct phenotypes in mice, H1047R being more severe than E545K. hGFAP-cre;H1047R mutants had severe hydrocephalus and died pre-weaning. In contrast all mice with the E545K allele survived through adulthood without hydrocephalus. Developmental analyses of hGFAP-cre;H1047R and Nestin-cre;E545K embryos revealed common mechanisms, such as larger neurons and lower cell densities, contributing to enlarged brain size, with differences more significant in H1047R mutants. E545K mutation also elevated cortical proliferation and cell cycle exit during late neurogenesis. We do not believe that overexpression of the transgenic H1047R allele versus the knock-in design of the E545K allele underlies the phenotypic differences. The PI3K enzyme is made of p110 (encoded by Pik3ca) and p85 subunits. p110 stability is entirely dependent on levels of p85 (Geering et al., 2007; Fruman et al., 2000; Yu et al., 1998) and we have not altered p85. Rather, the phenotypic differences more likely reflect distinct allele-specific overactivation of PI3K signaling. The H1047R mutation increases the level and duration of response to extracellular ligand, while E545K alters the helical domain resulting in constitutive low level signaling with a blunted response to extracellular ligands (Miled et al., 2007; Zhao and Vogt, 2008).

These differences likely reflect distinct mechanisms differentially altering PI3K signaling. Whereas H1047R mutation increases the level and duration of response to extracellular ligand, E545K alters the helical domain resulting in constitutive low level signaling with a blunted response to extracellular ligands (Miled et al., 2007; Zhao and Vogt, 2008).

Effect of Pik3ca overactivation on brain and cell size is temporally regulated

By activating the E545K mutation in progressively limited progenitor pools, we decreased the size of brain and cells in a graduated fashion. Postnatal E545K activation had no impact on cell/brain size. We conclude that the PIK3CA-related brain overgrowth must arise from mosaic mutations in embryonic neural progenitors.

Although neuronal size was enlarged in both hGFAP-cre;H1047R and Nestin-cre;E545K mutants, it was less than that observed in Pten null mice or in cultured hippocampal neurons constitutively overexpressing Akt (Kumar, 2005; Kwon et al., 2001). Multiple models of Pten deletion cause progressive increases in postnatal neuronal size and increased brain size without continued proliferation (Kwon et al., 2001; Fraser, 2004; Fraser et al., 2008; Backman et al., 2001). Our Nestin-cre;E545K mutants had enlarged brain size evident at birth, without progressive increases in postnatal cell size. This is congruent with the analysis of resected human brain tissue from SEGCD patients. Mild cellular enlargement was observed with PIK3CA mutations in contrast to marked enlargement with PTEN or AKT3 mutations (Jansen et al., 2015).

Aberrant neuronal migration is a major contributor to Pik3ca-related cortical dysplasia

Brains of SEGCD patients show mild to moderate migration defects in early-born cortical neurons and more severe defects in late-born neurons (Arai et al., 2012; Rossini et al., 2014). Similarly, embryonic activation of H1047R and E545K in mice caused abnormal neocortical lamination, with late-migrating Cux1-positive neurons severely affected in both the mutants. Birthdating studies support the conclusion that Pik3ca activation does not alter cell fate and that cortical dysplasia is predominantly a result of aberrant migration. The severity of dyslamination in H1047R mutants likely reflects the dysplastic Reelin-positive Cajal-Retzius cells. However the Reelin-positive layer remained well defined in both mutants. This is in contrast to the ectopic Reelin expression in neurons expressing high levels of overactive pAKT introduced by electroporation into embryonic mouse cortex (Baek et al., 2015). In human SEGCD, late migrating neurons often fail to migrate to the upper layers (Arai et al., 2012), a phenotype more severe than seen in any of our mouse models. However, NeuN immunohistochemistry in H1047R mutants confirmed the presence of ectopic neurons in the subcortical white matter, as seen in human SEGCD brain (Arai et al., 2012; Salamon, 2006). Human MEG is associated with a wide range of white matter dysplasia ranging from agenesis of corpus callosum to thickening of subcortical axon bundles (Conway et al., 2007; Adamsbaum et al., 1998; De Rosa et al., 1992; Jansen et al., 2015; Salamon, 2006). These features were also faithfully recapitulated in our mouse models.

Pik3ca-related epilepsy is an active Pik3ca-dependent process dissociable from dysmorphology

Both adult megalencephaic Nestin-cre;E545K and normocephalic Nestin-creER;E545K mice exhibited spontaneous seizures as well as lowered seizure thresholds upon PTZ-seizure induction. Although cortical dysplasia resulted from embryonic activation of Pik3ca in Nestin-cre;E545K mice, postnatal activation of Nestin-creER;E545K did not cause increased cell size or megalencephaly or altered cortical lamination. Thus Pik3ca-dependent epilepsy is independent of dysmorphology. Further, inhibitory interneurons were not grossly perturbed in Nestin-creER;E545K mice (data not shown). This is congruent with the fact that these interneurons are born at embryonic stages and their migration is almost complete before birth (Batista‐Brito and Fishell, 2009). Therefore altered interneuron development in Nestin-cre;E545K may contribute to epilepsy, aberrant interneuron development cannot represent a common mechanism for epilepsy in both models. The observation that acute BKM120 treatment is sufficient to inhibit PTZ-induced seizures even in adult megalencephalic mice supports the argument that the epileptic seizures are independent of dysplasia since the latter is not reversed over the short course of treatment. This is an important finding since a large portion of FCD patients who do not show detectable dysplasia suffer from intractable epilepsy (Bernasconi et al., 2011).

Proteomic analyses of cell signaling networks in megalencephalic cortical and hippocampal tissue at baseline and treated with PTZ and/or BKM120 provide insight into the mechanism of Pik3ca-dependent epilepsy. Nestin-cre;E545K mutants had elevated PI3K signaling with a more robust upregulation of mTOR-dependent pS473-Akt than the direct PDK1-dependent pT308-Akt, similar to the recent findings in human brain samples with PIK3CA mutations (Jansen et al., 2015). The modest changes in signaling compared to controls is congruent with previous studies which demonstrated only modest changes in the steady-state levels of PI3K signaling in breast cancer cells with PIK3CA mutations (Stemke-Hale et al., 2008). Higher signaling levels in hippocampus versus cortex suggest a more prominent role of hippocampus in the seizure phenotype. PTZ administration alone in both controls and megalencephalic Nestin-cre;E545K mutants caused upregulation of many core components of PI3K-AKT pathway, including pAkt, pS6 and pNDRG1. This is congruent with a report showing PTZ-induced seizures in rats upregulated PI3K-AKT-mTOR pathway (Zhang and Wong, 2012) and suggests that elevated baseline PI3K signaling levels are epileptogenic.

Indeed, there is extensive human and mouse evidence that elevated mTOR signaling is epileptogenic although the mechanisms for the epilepsy are incompletely understood. A number of mechanisms including altered development, cell size, growth, proliferation and circuitry have been reported (Wong and Crino, 2012). Most remarkably however, our acute BKM120 administration data clearly demonstrates that histopathological mechanisms are not the primary epilepsy drivers. Acute 1 hr of BKM120 administration was sufficient to completely inhibit the increased phosphorylation levels induced by PTZ, notably returning mutant hippocampal mTOR-dependent pS473-AKT levels to baseline untreated control levels. This was sufficient to normalize the PTZ-seizure induction threshold, despite continued dysplasia in Nestin-cre;E545K mutants. We conclude that elevated PI3K signaling is itself actively epileptogenic, independent of underlying developmental pathology.

Changing the face of intractable pediatric epilepsy

The discovery that Pik3ca-related epilepsy is independent of dysplasia and susceptible to acute modulation is a major and paradigm shifting finding. Since PIK3CA resides at the top of the PI3K-AKT pathway, our mouse models represent surrogates for the entire group of patients with segmental brain overgrowth, including patients with somatic mosaic mTOR and AKT3 mutations (Keppler-Noreuil et al., 2014; Lee et al., 2012; D'Gama et al., 2015; Conway et al., 2007; Jansen et al., 2015; Mirzaa et al., 2012). SEGCD is associated with early onset, severe and frequently intractable epilepsy that responds poorly to standard seizure medications (Bast et al., 2006; Fauser et al., 2015; Fauser, 2006; Pasquier et al., 2002; Russo et al., 2003; Tassi, 2002). Epilepsy surgery has been comparatively more successful (73%) in combating seizures in the same children (Fauser et al., 2015). A drug-based therapy however, would clearly be preferable. mTOR inhibition with rapamycin has shown therapeutic promise in FCD patients and animals models (Baek et al., 2015; Curatolo and Moavero, 2013; Lim et al., 2015; Moon et al., 2015); however, rapamycin treatments are not acute. Our data demonstrates that acute small molecule-based modulation of PI3K signaling, despite the presence of dysplasia, has dramatic therapeutic benefit. This suggests that PI3K inhibitors offer a promising new avenue for effective antiepileptic therapy for large cohorts intractable pediatric epilepsy patients.

Materials and methods

Mice

The following mouse lines were used: Nestin-cre (Jackson Labs, Bar Harbor, Maine, USA; Stock #003771), Nestin-creERT2 lines (Jackson Laboratory, Bar Harbor, Maine, USA, MGI:3641212 and line generated in SJB’s lab, Zhu et al., 2012), human glial fibrillary acidic protein (hGFAP)-cre (Jackson Labs, Stock #004600), Pik3caH1047R transgenic (human H1047R transgene expression is under the control of a tetracycline-inducible promoter (TetO)) (Liu et al., 2011), Rosa26-rtTA line (Jackson Labs, Stock #005670), Pik3caE545K knock-in (Robinson et al., 2012), Ai-9 (Jackson Labs, Stock #007905), Ai-14 (Jackson Labs, Stock #007914), R26-LSL-EYFP (Jackson Labs, Stock #006148), Rosa26-LacZ (Jackson Labs, Stock #003474). We have designated the Pik3caH1047R and Pik3caE545K conditional mutant mice as H1047R and E545K mutants/lines throughout the manuscript.

All lines were maintained on a mixed genetic background, comprising of FVB, C57Bl6, 129 and CD1 strains. Noon of the day of vaginal plug was designated as embryonic day 0.5 (E0.5). The day of birth was designated as postnatal day 0 (P0). The H1047R and Rosa26-rtTA lines were intercrossed and female mice positive for both these alleles were crossed with hGFAP-cre;RosartTA;Pik3caH1047R males. To ensure that cre and Pik3caH1047R mutant transgene expression was correlated plugged females were treated with doxycycline (Sigma; 2 mg/ml) from E0.5 available ad libitum in drinking water. For the neonatal induction experiment, the pups were treated with doxycycline from P1. The E545K line was crossed to reporter lines to obtain E545K floxed allele and the reporter in the same mouse line. Tamoxifen (Sigma T5648) was dissolved at 37°C in corn oil (Sigma) at 5 mg/ml and was administered intraperitoneally to pups of the cross Nestin-creER X Pik3caE545K mice at a dose of 75 μg/g body weight, once a day at P0 and P1, to activate the E545K mutation postnatally. hGFAP–cre, Nestin–cre and Nestin–creERT2 mice were genotyped by PCR using primers for the cre coding region, as previously described (Chizhikov, 2006). Genotyping of other alleles were done according to the following references: H1047R and Rosa+/- (Liu et al., 2011), E545Kfloxed/+ (Robinson et al., 2012), EYFP/+ and Ai9/+  (Zhu et al., 2012). All mouse procedures were approved by the Institutional Animal Care and Use Committees.

Sample preparation and histochemical procedures

Embryos and postnatal pups were harvested in phosphate buffer saline (PBS); brains fixed in 4% paraformaldehyde (PFA) for 4 hr, equilibrated in 30% (wt/vol) sucrose made in PBS, and sectioned at 25 μm on a freezing microtome. Adult mice were perfused with 4% PFA, brains collected and fixed in 4% PFA overnight, sunk in 30% sucrose in PBS, embedded in optimum cutting temperature (OCT) compound and sectioned at 12 μm on a cryostat. Sections were then processed for Nissl, hematoxylin and eosin (H&E) or immunohistochemical staining.

Immunohistochemistry: Sections were washed thrice in PBS, boiled in 10 mM Sodium citrate solution for antigen retrieval, blocked in 5% serum in PBS with 0.1%Triton X-100 and then incubated overnight at 4°C with primary antibodies. The next day, sections were washed thrice in PBS, incubated with appropriate species-specific secondary antibodies conjugated with Alexa 488, 568, 594 or 647 fluorophores (Invitrogen) for 2 h at room temperature and then counterstained with DAPI to visualize nuclei. Sections were coverslipped using Fluorogel (EMS #17985) mounting medium. Immunostained sections were imaged in Zeiss LSM 710 Imager Z2 laser scanning confocal microscope using Zen 2009 software and later processed in ImageJ software (NIH, Bethesda, Maryland, USA). Primary antibodies used are: rat anti-BrdU (Abcam), mouse anti-BrdU (Roche), rabbit anti-Tbr1(EMD Millipore), mouse anti-Tbr2 (EMD Millipore), rat anti-Ctip2 (Abcam), rabbit anti-Cux1/CDP (Santa Cruz Biotechnology), rabbit anti-pS6 (Cell Signaling), mouse anti-NeuN (EMD Millipore), mouse anti-Reelin (EMD Millipore), rabbit anti-Laminin (Sigma), rabbit anti-Olig2 (EMD Millipore), mouse anti-Nestin (EMD Millipore), chicken anti-YFP (Abcam), rabbit anti-Ki67 (Vector Lab), mouse anti-S100 (Abcam).

Nissl and H&E staining: Sections were stained in 0.1% cresyl violet solution for 10 min, rinsed quickly in distilled water, dehydrated in 95% ethanol, and left in xylene before being coverslipped with Permount (Fischer Scientific). H&E staining was performed by passing the sections through Harris modified Hematoxylin solution (Fisher Scientific) and EosinY (Sigma) and then dehydrating them in increasing grades of ethanol before dipping in xylene and coverslipping. Brightfield images were taken in Leica MZFLIII microscope using Leica DFC425 camera and LAS V3.8 software.

BrdU incorporation experiments

Bromodeoxyuridine (BrdU; Life Technologies) was administered intraperitoneally (100 μg/g of body weight) to pregnant mice at E14.5/16.5 for 1 hr, at E15.5 for 1 day and at E12.5/E16.5 for proliferation assays, cell cycle exit and birthdating experiments respectively. S-phase labeling index (LI) was calculated by dividing total BrdU+ cells by total number of DAPI+ cells. Quit fraction was calculated by dividing BrdU+Ki67 cells by total number of BrdU+ cells.

β-Gal staining protocol 

Brain sections were briefly fixed, washed in wash buffer at room temperature and then stained overnight at 37°C in the staining solution comprising of the X-gal substrate. The sections were then washed in wash buffer at room temperature and stored at 4°C.

TUNEL staining

TUNEL staining was processed on E16.5 control and mutant sections using Roche In situ Cell Death Detection Kit, Fluorescein.

Magnetic resonance imaging (MRI) for volumetric analysis

At least 5 mice of each genotype (age P40–60) were used for volumetric analyses. MRI study was performed using a 7 T Bruker ClinScan system (Bruker BioSpin MRI GmbH, Germany) equipped with 12S gradient coil. A 2-channel surface coil was used for MR imaging. Animals were anesthetized and maintained with 1.5% isoflurane during MRI sessions. Transverse T2-weighted turbo spin echo images were acquired for volume measurements (TR/TE = 3660/50 ms, FOV = 25 × 25 mm, matrix = 320 × 320, NEX = 1, thickness = 0.4 mm, scan time = 6.5 min). Total brain volumes were obtained by manually segmenting brain regions from olfactory bulbs to cerebellum, and computing volumes using OsiriX (Pixmeo, Switzerland). Each data point in the graph represents 1 mouse.

Seizure experiments

Mice obtained from the following crosses were used for experiments at ~P35 (young age) and ~P180 (old age): Nestin-cre/+ X Pik3caE545Kfloxed/+ and Nestin-creER/+ X Pik3caE545Kfloxed/+. At least 5 animals of each genotype were used per treatment experiment.

Pentylenetetrazole (PTZ) seizure test. Mice were subcutaneously injected with PTZ (Sigma), a GABA (A) receptor-antagonist, at 40 mg/kg body weight and digital videos of the mice were recorded for 30 min post-PTZ injection. Principal behavior in each 10 second-bin of the recorded video was scored as 4 or 5 using the Racine scale of seizure severity (4, rearing with forelimb clonus; and 5, rearing and falling with forelimb clonus) (Kalume, 2013; Racine, 1972). Treatment trials. Pan-PI3K inhibitor BKM-120 (Novartis; 50 mg/kg body weight, dissolved in 0.5% Tween-80, 0.5% methylcellulose) or saline was administered by oral gavage to the mice 1hr before PTZ seizure test.

Sleep deprivation (SD). To permit control of circadian variations of sleep in these experiments, baseline (control) sleep data (Pre SD) were recorded from mice one day before they were submitted to total sleep deprivation. Mice were allowed to sleep normally for 5 continuous hours beginning at 8:00 AM, and then baseline sleep video-EEG recordings were obtained continuously in the 1 subsequent hour. On the following day, beginning at 8:00 AM, the same mice were kept awake for 5 consecutive hours by random gentle touches with a rotating light curtain attached to a motor mounted on the lid of the sleep deprivation chamber. The motor was in turn, connected to a computer via Power Lab (ADInstruments, Colorado Spring, CO). The random direction and speed of the motor rotation were custom-programmed in the stimulator panel dialog box of LabChart 8 Software (ADInstruments, Colorado Spring, CO). The specific parameters used are tabulated as Supplementary file 1. Post sleep deprivation, mice were not disturbed and post SD recordings were obtained for 2hr.

Video-electroencephalagraphy-electromyography (Video-EEG-EMG) recording. These experiments were performed as previously described (Kalume, 2013). Briefly, mice underwent survival surgery to implant fine (diameter: 130 µm bare; 180 µm coated) silver wire EEG and EMG electrodes under isoflurane anesthesia. Four EEG electrodes were placed bilaterally through the small cranial burr holes over the posterior and frontal cortices and were fixed in place with cyanoacrylate glue and dental cement (Lang Dental Manufacturing Co., Inc., Wheeling, IL). Similarly, one reference electrode was placed above the cerebellum. A ground electrode was inserted subcutaneously over the back. EMG electrodes were placed in back muscles. Only 2 electrodes were implanted in the young Nestin-cre;E545K mutant and control mice. Mice were allowed to recover from surgery for 2-3 days. Simultaneous video-EEG-EMG recordings were collected from conscious mice on a PowerLab 8/35 data acquisition unit using LabChart 7.3.3 software (AD Instruments, Colorado Spring, Co). All bioelectrical signals were acquired at 1KHz sampling rate. The EEG signals were processed off-line with a 1-70 Hz bandpass filter and the ECG signals with a 3-Hz highpass filter. Interictal spikes were identified as transient, clearly distinguished from background activity, with pointed peak and short duration. Myoclonic seizures were identified as shock-like jerks of the muscles on video associated with a spike or polyspike-wave complex on EEG.

Reverse phase protein array (RPPA) analysis

Cortex and hippocampus were dissected out of P35 control and E545K mutant mice, following different treatments (vehicle only (-), +BKM120, +PTZ, BKM120+PTZ), and flash-frozen in liquid nitrogen then sent to the RPPA Core Facility at MD Anderson Cancer Center, University of Texas. Three independent biological replicates per sample were analyzed. Analysis was performed as previously described (Tibes et al., 2006). The mouse brain tissue samples were lysed and underwent protein extraction. Cellular protein was denatured by SDS sample buffer and serial dilution was made for each sample. Cell lysates were then probed with different validated antibodies. Signals were detected by DAB colorimetric reaction and intensity was quantified using ArrayPro software. Protein concentration was determined by super curve fitting. All the data points were normalized for protein loading and transformed to linear value. These linear values were used to make bar graphs for comparative analysis. See http://www.mdanderson.org/education-and-research/resources-for-professionals/scientific-resources/core-facilities-and-services/functional-proteomics-rppa-core/index.html) for a detailed antibody list and protocols.

Quantitative analysis

For quantitative analysis of embryos, data was collected from comparable sections of a minimum of 3 embryos of each genotype (from 2 or more independent litters) at each developmental stage. Cortical length was measured in the lateral ventricular lining from the tip of the fimbria/cortical hem to the pallial-subpallial boundary. Cortical length and thickness were measured using ImageJ software (NIH, Bethesda, Maryland, USA); the data was normalized to the control value. Cell counts from E14.5 and E16.5 brains were obtained from 25% of the neocortex. Area of interest was derived by dividing the whole length of neocortex into quarters and then taking images of the total area, from pia to ventricle, in the third quartile from dorsal midline. Confocal stacks of immunostained sections of each developmental stage were generated by scanning at intervals of 0.99 μm using filters of appropriate wavelengths at 20X and 40X magnifications. Confocal images of DAPI-stained brain sections and NeuN/pS6-immunostained sections were used to measure nuclear and cell size respectively. Measurements for labeling index, quit fraction, birthdating studies, cell density and size were calculated using ImageJ. For zonal quantification of cells, the cortical column was divided into 5 different parts – the ventricular-subventricular zone (vz/svz), white matter, and 3 equally divided zones of the neocortical plate (lower, mid, upper).

Statistical significance was assessed using 2-tailed unpaired t-tests (for cortical length and thickness, cell density, nuclear size, TUNEL assay, labeling index, quit fraction, total cell counts and seizure data) and ANOVA followed by Bonferroni (for cell size, BKM treatment data, birthdating experiments) and Tukey (for RPPA graphs) post-tests. These analyses were performed in GraphPad Prism v5.01 (GraphPad Software Inc., San Diego, USA) or in Igor Pro v6.3.6.4, Igor Pro Software, Lake Oswego, USA. Differences were considered significant at P< 0.05.

References

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
    Electroencephalography
    1. CD Binnie
    2. PF Prior
    (1994)
    Journal of Neurology, Neurosurgery & Psychiatry 57:1308–1319.
    https://doi.org/10.1136/jnnp.57.11.1308
  10. 10
  11. 11
  12. 12
  13. 13
  14. 14
  15. 15
  16. 16
  17. 17
  18. 18
  19. 19
  20. 20
  21. 21
  22. 22
  23. 23
  24. 24
  25. 25
  26. 26
  27. 27
  28. 28
  29. 29
    Rare cancer-specific mutations in PIK3CA show gain of function
    1. M Gymnopoulos
    2. M-A Elsliger
    3. PK Vogt
    (2007)
    Proceedings of the National Academy of Sciences of the United States of America 104:5569–5574.
    https://doi.org/10.1073/pnas.0701005104
  30. 30
  31. 31
  32. 32
    Genetic analysis of benign, low-grade, and high-grade ovarian tumors
    1. H Iwabuchi
    2. M Sakamoto
    3. H Sakunaga
    4. YY Ma
    5. ML Carcangiu
    6. D Pinkel
    7. TL Yang-Feng
    8. JW Gray
    (1995)
    Cancer Research 55:6172–6180.
  33. 33
  34. 34
  35. 35
  36. 36
  37. 37
  38. 38
  39. 39
  40. 40
  41. 41
  42. 42
  43. 43
  44. 44
  45. 45
  46. 46
  47. 47
  48. 48
  49. 49
  50. 50
  51. 51
  52. 52
  53. 53
  54. 54
    Surgical pathology of drug-resistant partial epilepsy. a 10-year-experience with a series of 327 consecutive resections
    1. B Pasquier
    2. M Péoc'H
    3. B Fabre-Bocquentin
    4. L Bensaadi
    5. D Pasquier
    6. D Hoffmann
    7. P Kahane
    8. L Tassi
    9. JF Le Bas
    10. AL Benabid
    (2002)
    Epileptic Disorders 4:99–119.
  55. 55
  56. 56
  57. 57
  58. 58
  59. 59
  60. 60
    Focal cortical resection in malformations of cortical development
    1. GL Russo
    2. L Tassi
    3. M Cossu
    4. F Cardinale
    5. R Mai
    6. L Castana
    7. N Colombo
    8. M Bramerio
    (2003)
    Epileptic Disorders 5 Suppl 2:S115–S123.
  61. 61
  62. 62
  63. 63
  64. 64
  65. 65
  66. 66
  67. 67
  68. 68
  69. 69
  70. 70
  71. 71
  72. 72
  73. 73
  74. 74

Decision letter

  1. Sean J Morrison
    Reviewing Editor; Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, United States

eLife posts the editorial decision letter and author response on a selection of the published articles (subject to the approval of the authors). An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent (see review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.

Thank you for choosing to send your work entitled "Mouse models of human PIK3CA-related segmental overgrowth have treatment-responsive epilepsy" for consideration at eLife. Your full submission has been evaluated by Sean Morrison (Senior Editor) and three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the decision was reached after discussions between the reviewers. Based on our discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife.

In particular, while all three reviewers agreed that the work was potentially of interest, they felt that the characterization of the developmental phenotype was insufficient, and that it would require extensive new experimentation to make it rigorous enough for publication. In addition, the reviewers were concerned about the lack of insight into the epilepsy phenotype, with regard to cell biological mechanisms.

Reviewer #1:

In this manuscript by Roy et al., the authors have examined the effects of hyperactivating PI3-kinase mutations on neural development, have compared these effects to those seen in humans carrying similar mutations, and have shown that inhibition of PI3-kinase activity can rescue the seizure phenotype seen in adult mice. In general, this is a nicely-performed study and the conclusions are interesting from a variety of perspectives. However, this manuscript could be significantly improved by a consideration of the following issues.

1) The authors have used a number of Cre driver lines to look at two different activating mutations in PIK3CA, H1047R and E545K. However, the strategies for driving expression of these mutant alleles are very different, with the former involving tet-inducible gene expression and the latter a cre-dependent knock-in allele. Since the E545K strategy mimics the human congenital mutations that the authors seek to model, and the H1047R is essentially an overexpression study and thus not as relevant, then the authors should really emphasize (and show) all of their findings with the E545K mutant, even though in many cases the differences are not as dramatic. For example, the experiments documenting neuronal colocalization with E545K are all shown in the supplementary data while those with the H1047R mutant are shown in the body of the paper in Figure 4. This should be reversed.

2) Some of the most interesting comparisons in this manuscript are those looking at different timepoints when the activating allele is expressed. However, in order to validate these comparisons, the authors need to show a comparison of the level of recombination that they are driving. I know that these are well-characterized cre driver lines, but having said that, there has been some drift with a number of these lines (for example the Nestin-cre mouse used here), and the authors really should provide their own data to validate the mutants they are studying.

3) The section on neuronal mislocalization is very interesting, but needs to be strengthened in a number of additional ways. First, the authors need to provide some kind of quantification, focusing on the E545K mutants, to solidify their data. This could be as simple as dividing the cortex into zones/layers (depending upon the age), and quantifying the proportion of layer-specific marker-positive cells that are in the different zones/layers in controls versus mutants. Second, the authors should remove their references to neuronal migration. They don't actually study migration anywhere in this manuscript, but instead study localization of neurons. Since, as they indicate in the discussion, these phenotypes could be due to many different developmental perturbations, to indicate that they are due to neuronal migration deficits is misleading.

4) The approach of RPPA to scan a large number of signaling proteins at once is a valuable one. Nonetheless, it is important that these changes be validated using other approaches. In particular, the authors should choose at least a few of the more important changes and verify them using western blots. If they all match the data obtained using RPPA, then this will validate the entire approach for these particular samples.

Reviewer #2:

In this study the authors create animal models of megalencephaly (MEG) that are associated with mutations in PIK3CA. They first show that overexpression of PIK3CA in neural progenitors disrupts normal cortical development, and demonstrate that the timing of transgene activation is a critical feature of disease severity. They also demonstrate that overexpression of the two PIK3CA alleles leads to increased size of the cortex that is generally associated with an increase in nuclear and cell size and a decrease in cell density. They then demonstrate that the expanded cortex displays defects in lamination. As a consequence, transgenic animals overexpressing active alleles of PIK3CA are more prone to epileptic seizures. Finally, the authors show that a class I PI3K inhibitor has anti-seizure effects, and reduces phosphorylation of PI3K pathway components.

1) Validation of animal models. The authors need to show exactly when and where the p110a transgenes are expressed by their Nestin-cre, Nestin-creER and hGFAP-cre driver lines. Could there be differences in phenotypes from these different cre drivers based on level of expression, rather than simply due to the timing of cre activation? Also, the timing of tamoxifen administration for nestin-creER should be given in the results section to know when the transgenes were induced with this driver.

2) Comparisons of animal models. The authors do a nice job of presenting the different phenotypes associated with overexpression of the E545K allele achieved with the different cre drivers, but it would help to have more information on the H1047R allele. How does overexpression of H1047R affect brain size and morphology with the Nestin-creER and Nestin-cre lines? The authors stated that the most severe phenotype was achieved in hGFAP-cre;H1047R mtuants, but relative to what? To the other H1047R lines, or relative to E545K lines (or both)? If H1047R was only tested with the hGFAP-cre line, this should be clearly stated.

Reviewer #3:

This manuscript describes the phenotype of mouse models with mutations in PIK3CA that should overactivate the PI3K-AKT pathway in the nervous system. The E545K and H1047R activating mutations have been found before in patients with cancer, but also with various forms of segmental cortical dysplasia. Corresponding mouse lines have been generated and investigated before for studying the role of these activating mutations in cancer. In this study, the authors have used Nestin-Cre and GFAP-Cre for nervous system-specific induction of the mutant alleles, and these mice developed enlarged brain size, cortical dysplasia and epilepsy. The authors find that GFAP-Cre H1047R mutants show a very severe phenotype with progressive hydrocephalus and death around birth. Mice with E545K mutation and the same GFAP-Cre driver were less affected. Earlier developmental induction of the E545K mutation with Nestin-Cre showed a more severe phenotype than that observed after GFAP-Cre-mediated activation. The authors then found that the inner cortical length of GFAP-Cre H1047R mutants at E14-E16 was longer than in controls. Surprisingly, increased proliferation was not observed in these animals, only enlarged cell size. Interestingly, the Nestin-Cre E545K mutants showed enhanced proliferation with reduced cortical thickness, indicating that the newborn cells did not adequately migrate. The authors also observed dysplastic Cajal-Retzius cells in GFAP-Cre H1047R mice at E16. They then investigated Nestin-Cre and Tamoxifen-inducible Nestin-Cre E545K mutant mice for abnormalities in EEG and found signs of epileptiform activity, in particular when induced with the GABA-A receptor antagonist PTZ. The authors then also provide evidence that the PI3K inhibitor BKM-120 suppresses seizure activity and shows some effects on parameters of PI3K pathway activation.

Although these data are of potential interest to understand the molecular basis of segmental cortical dysplasia in humans, the paper is largely descriptive and the mechanisms how PI3K activation induces this complex disorganization of cortical development that then results in altered excitability and epileptic seizures is not explained. It is even unclear whether alterations in cell division, cell cycle exit, migration, terminal differentiation, spontaneous activity and synaptic plasticity occur in these mice. It is unclear whether GFAP-Cre and Nestin-Cre act in the same or in distinct precursor cell populations, whether defects in all types of neurons, or only specific subtypes, or defects in astrocytes cause this specific phenotype. The latter is possible in particular in GFAP-Cre mice. The previous paper by Robinson et al. in Nature 2012 showed that the same E545K mutation, when induced with Blbp-Cre in lower rhombic lip progenitors accelerates tumor generation, but does not per se initiate WNT subgroup medulloblastoma. This leaves the question open whether the same mutation in Nestin- or GFAP-Cre expressing cells causes defects that need additional signals to develop the pathogenic phenotype.

Additional specific comments:

1) The paper lacks clear evidence about the types of cells in which the mutant PIK3CA isoforms are expressed, and at which stage of development recombination occurs. This is necessary to explain whether dysregulated PIK3CA causes abnormalities in division of neural precursor cells. I wonder why the authors did not do more detailed pulse chase experiments with BrdU to study potential effects on altered proliferation of different types of precursor cells in the ventricular and subventricular zone. It would also be important to know whether proliferation of neuronal cells is differentially affected in comparison to proliferation of astrocytic precursor cells. At E16.5, the time point when the analyses shown in Figure 2 were performed, proliferation of astrocytes has already started, and the authors should do the studies shown in Figure 3 with markers that can distinguish neuronal from astrocytic precursor cells.

2) It is hard to explain why the cell density, as shown in Figure 3p is reduced when BrdU incorperation is increased. It is also not clear in which layers of the cortex the authors observe this reduced cell density at E16.5. To understand this phenotype, the VZ/SVZ, the mantle zone and the intermediate zone should be investigated separately. Did the authors also investigate whether there is enhanced loss of cells by apoptosis or other types of cell death between E14.5 and E16.5 to explain this phenotype?

3) The phenotype with increased cell size is hard to explain. This could be due to a defect in the cell fate determination of distinct populations of neuronal types, for example when generation and survival of pyramidal cells in comparison to interneurons is enhanced, or also by altered generations of neurons in comparison to glial cells. In order to understand the phenotype of altered cortical morphology and enhanced epileptic seizures, this would be important to know.

4) There is a big gap between the defects in cortical thickness and the potential mechanisms that could explain the altered threshold for epileptic seizures. Is there a dysbalance between GABAergic and glutamatergic neurons and synapses in the brain of these mice? Is there defective regulation of synapse generation, function and plasticity? Are there defects in dendritic arborization and synaptogenesis? Are there differences in the morphology of astrocytes and differences in gene expression in such astrocytes, i.e. for neurotransmitter transporters, that could explain the epileptiform activity?

5) It is not clear whether the enhanced epileptiform activity reflects a developmental defect or altered synaptic activity, which is directly driven by altered PIK3CA activation. The authors have used both a constitutive Nestin-Cre and a Tamoxifen-inducible Cre driver, but there are no data to distinguish the phenotype when E545K mutant PIK3CA is expressed from developmental stages, or only after acute induction in the adult.

Other questions and points of concern:

1) In the Materials and methods section, the authors say that all mouse lines were maintained on a mixed genetic background. It is not clear what this means and whether differences in genetic background could influence the phenotype. How can the authors exclude the possibility that the more severe phenotype observed in the GFAP-Cre drivers in comparison to Nestin-Cre drivers is due to different genetic background?

2) The data shown in Figure 5d are very hard to understand and not well described. What is the function of time at which the numbers of seizures occur? Does the diagram mean seizures within one minute? These bars lack standard deviations. How can one understand i.e. 0.4 seizures or 1.6 seizures per minute and why does the number of seizures fluctuate with a peak at 7 min., 15 and 22 min. after PTZ injection? Which phase of seizure activity is affected by BKM-120-treatment? Obviously, the PI3K inhibitor does not reduce seizure activity completely.

3) The data shown in Figure 6 are hard to understand, given that the differences are generally much lower than expected, and it is also not clear which types of cells and which subpopulations of neurons are predominantly affected by altered Akt phosphorylation or other downstream signaling parameters that are expected to be altered when the PI3-K pathway is constitutively activated.

https://doi.org/10.7554/eLife.12703.025

Author response

Reviewer #1:

In this manuscript by Roy et al., the authors have examined the effects of hyperactivating PI3-kinase mutations on neural development, have compared these effects to those seen in humans carrying similar mutations, and have shown that inhibition of PI3-kinase activity can rescue the seizure phenotype seen in adult mice. In general, this is a nicely-performed study and the conclusions are interesting from a variety of perspectives. However, this manuscript could be significantly improved by a consideration of the following issues. 1) The authors have used a number of Cre driver lines to look at two different activating mutations in PIK3CA, H1047R and E545K. However, the strategies for driving expression of these mutant alleles are very different, with the former involving tet-inducible gene expression and the latter a cre-dependent knock-in allele. Since the E545K strategy mimics the human congenital mutations that the authors seek to model, and the H1047R is essentially an overexpression study and thus not as relevant, […]

The H1047R allele is not functionally an overexpression allele. The PI3K enzyme is made of p110 (encoded by Pik3ca) and p85 subunits. Previous publications have demonstrated that p110 stability is dependent on levels of p85 (Fruman et al., 2000; Yu et al., 1998). Geering et al., 2007 demonstrated that there is no evidence of free p110 or free p85 subunits in mammalian cell lines and tissues. Thus, both the E545K and H1047R alleles are relevant to model human PIK3CA mutations.

[…] then the authors should really emphasize (and show) all of their findings with the E545K mutant, even though in many cases the differences are not as dramatic. For example, the experiments documenting neuronal colocalization with E545K are all shown in the supplementary data while those with the H1047R mutant are shown in the body of the paper in Figure 4. This should be reversed.

We have included data from both alleles throughout the main figures.

2) Some of the most interesting comparisons in this manuscript are those looking at different timepoints when the activating allele is expressed. However, in order to validate these comparisons, the authors need to show a comparison of the level of recombination that they are driving. I know that these are well-characterized cre driver lines, but having said that, there has been some drift with a number of these lines (for example the nestin-cre mouse used here), and the authors really should provide their own data to validate the mutants they are studying. We have included cre control data as Figure 1—figure supplement 2

3) The section on neuronal mislocalization is very interesting, but needs to be strengthened in a number of additional ways. First, the authors need to provide some kind of quantification, focusing on the E545K mutants, to solidify their data. This could be as simple as dividing the cortex into zones/layers (depending upon the age), and quantifying the proportion of layer-specific marker-positive cells that are in the different zones/layers in controls versus mutants.

We provide extensive new quantitation in Figure 6.

Second, the authors should remove their references to neuronal migration. They don't actually study migration anywhere in this manuscript, but instead study localization of neurons. Since, as they indicate in the discussion, these phenotypes could be due to many different developmental perturbations, to indicate that they are due to neuronal migration deficits is misleading. Our new birthdating experiments (Figure 6) now provide extensive support for migration deficits.

4) The approach of RPPA to scan a large number of signaling proteins at once is a valuable one. Nonetheless, it is important that these changes be validated using other approaches. In particular, the authors should choose at least a few of the more important changes and verify them using western blots. If they all match the data obtained using RPPA, then this will validate the entire approach for these particular samples.

The amount of mutant tissue available from the brain of the mice was limiting, particularly given the different assays that were performed on the tissues. RPPA requires very small amounts of tissue to perform multiplex analysis across many antibodies and was thus the most tissue sparing approach available. Several studies have demonstrated that RPPA is more sensitive than standard Western blotting and is becoming a standard assay in cancer biology (Akbani et al., 2014; Tibes et al., 2006; Gujral et al., 2013; Hennessy et al., 2010; Nishizuka et al., 2003). Indeed the RPPA facility has used this specific panel on more than 100,000 samples (Gordon Mills, our co-author, runs this facility and has published extensively on RPPA). Well over 100 papers including almost all of the TCGA (The Cancer Genome Atlas project) papers have used RPPA analysis and indeed, no confirmation western blots have been requested for the complete TCGA set due to the extensive validation in other sample sets. The three independent biological replicates per sample further support data validity. Unfortunately, insufficient mutant brain tissue was available to perform western blots at the end of the study and thus we had to rely on the results from the RPPA analysis.

Reviewer #2:

In this study the authors create animal models of megalencephaly (MEG) that are associated with mutations in PIK3CA. They first show that overexpression of PIK3CA in neural progenitors disrupts normal cortical development, and demonstrate that the timing of transgene activation is a critical feature of disease severity. They also demonstrate that overexpression of the two PIK3CA alleles leads to increased size of the cortex that is generally associated with an increase in nuclear and cell size and a decrease in cell density. They then demonstrate that the expanded cortex displays defects in lamination. As a consequence, transgenic animals overexpressing active alleles of PIK3CA are more prone to epileptic seizures. Finally, the authors show that a class I PI3K inhibitor has anti-seizure effects, and reduces phosphorylation of PI3K pathway components.

1) Validation of animal models. The authors need to show exactly when and where the p110a transgenes are expressed by their nestin-cre, nestin-creER and hGFAP-cre driver lines. Could there be differences in phenotypes from these different cre drivers based on level of expression, rather than simply due to the timing of cre activation? Also, the timing of tamoxifen administration for nestin-creER should be given in the results section to know when the transgenes were induced with this driver.

Cre validation is now provided in Figure 1— figure supplement 2.

Figure 1 clearly shows that it is not the cre line that affects the phenotype per se. It is the nature of the specific mutant allele as well as the time of activation of the mutation in brain that result in the developmental phenotypes. For example, if we compare the E545K and H1047R mutants, both activated by hGFAP-cre, we observe that the hGFAP-cre;H1047R mutant has hydrocephalus and agenesis of corpus callosum, while neither of these phenotypes are observed in hGFAP-cre;E545K mutant.

2) Comparisons of animal models. The authors do a nice job of presenting the different phenotypes associated with overexpression of the E545K allele achieved with the different cre drivers, but it would help to have more information on the H1047R allele. How does overexpression of H1047R affect brain size and morphology with the Nestin-creER and nestin-cre lines? The authors stated that the most severe phenotype was achieved in hGFAP-cre;H1047R mtuants, but relative to what? To the other H1047R lines, or relative to E545K lines (or both)? If H1047R was only tested with the hGFAP-cre line, this should be clearly stated.

We have rephrased this in the text. We meant among all the mutants studied in this paper, irrespective of allele or cre line, hGFAP-cre;H1047R mutants show the most severe developmental defects in the brain.

Reviewer #3:

This manuscript describes the phenotype of mouse models with mutations in PIK3CA that should overactivate the PI3K-AKT pathway in the nervous system. The E545K and H1047R activating mutations have been found before in patients with cancer, but also with various forms of segmental cortical dysplasia. Corresponding mouse lines have been generated and investigated before for studying the role of these activating mutations in cancer. In this study, the authors have used Nestin-Cre and GFAP-Cre for nervous system-specific induction of the mutant alleles, and these mice developed enlarged brain size, cortical dysplasia and epilepsy. The authors find that GFAP-Cre H1047R mutants show a very severe phenotype with progressive hydrocephalus and death around birth. Mice with E545K mutation and the same GFAP-Cre driver were less affected. Earlier developmental induction of the E545K mutation with Nestin-Cre showed a more severe phenotype than that observed after GFAP-Cre-mediated activation. The authors then found that the inner cortical length of GFAP-Cre H1047R mutants at E14-E16 was longer than in controls. Surprisingly, increased proliferation was not observed in these animals, only enlarged cell size. Interestingly, the Nestin-Cre E545K mutants showed enhanced proliferation with reduced cortical thickness, indicating that the newborn cells did not adequately migrate. The authors also observed dysplastic Cajal-Retzius cells in GFAP-Cre H1047R mice at E16. They then investigated Nestin-Cre and Tamoxifen-inducible Nestin-Cre E545K mutant mice for abnormalities in EEG and found signs of epileptiform activity, in particular when induced with the GABA-A receptor antagonist PTZ. The authors then also provide evidence that the PI3K inhibitor BKM-120 suppresses seizure activity and shows some effects on parameters of PI3K pathway activation. Although these data are of potential interest to understand the molecular basis of segmental cortical dysplasia in humans, the paper is largely descriptive and the mechanisms how PI3K activation induces this complex disorganization of cortical development that then results in altered excitability and epileptic seizures is not explained. It is even unclear whether alterations in cell division, cell cycle exit, migration, terminal differentiation, spontaneous activity and synaptic plasticity occur in these mice.

We concur that we have extensively described the first models of human PIK3CA related brain malformations – a clinically important class of cortical malformations with an impressive phenotypic spectrum – from dysplastic megalencephaly to focal cortical dysplasia. Our mouse models recapitulate the human phenotypes and demonstrate validity of our models. Further we demonstrate that the mice display epilepsy – perhaps the most clinically relevant phenotype in this population. Since these are the first models, extensive phenotypic description was required.

Mechanistically, we counter that we have indeed defined the developmental basis of megalencephaly and cortical dysplasia, showing alterations in proliferation, cell cycle exit, cell migration versus cell fate, and cell size (Figures 3, 6). While these phenotypes are important, the major significant finding of our work is that the cortical dysplasia is less relevant to epilepsy than previously thought. Developmentally, we can dissociate dysmorphology from epilepsy. Mice with abnormal neocortical cell distribution (Nestin-cre;E545K) as well as those without dysplasia (Nestin-creER;E545K) exhibit epilepsy. Further, we can acutely treat the epilepsy in mice even with severe dysplasia.

As we have now more lucidly argued in the Introduction and Discussion, the finding that Pik3ca-driven epilepsy is an active process, amenable to acute intervention is a major advance. Mechanistically, acute treatment with BKM120 alters mTOR-dependent phosphorylation of AKT with strong effects in the mutant hippocampus. Given the extensive developmental analyses presented in addition to the epilepsy data, we consider further analysis of the synaptic physiology and the dissection of pAKT-dependent and/or pAKT-independent pathways that underlie the epilepsy to be well beyond the scope of the current manuscript.

It is unclear whether GFAP-Cre and Nestin-Cre act in the same or in distinct precursor cell populations, whether defects in all types of neurons, or only specific subtypes, or defects in astrocytes cause this specific phenotype. The latter is possible in particular in GFAP-Cre mice.

Please see Figure 1—figure supplement 2 for differential expression pattern of hGFAP-cre and Nestin-cre lines. These two lines express in overlapping but distinct cell populations. Moreover, when we compare Nestin-cre;E545K and hGFAP-cre;E545K we see they have comparable morphological phenotypes while hGFAP-cre;H1047R is quite different. This confirms that differential phenotype is dependent on the specific mutant allele even when same cre line is used.

The previous paper by Robinson et al. in Nature 2012 showed that the same E545K mutation, when induced with Blbp-Cre in lower rhombic lip progenitors accelerates tumor generation, but does not per se initiate WNT subgroup medulloblastoma. This leaves the question open whether the same mutation in Nestin- or GFAP-Cre expressing cells causes defects that need additional signals to develop the pathogenic phenotype.

We are unclear regarding the nature of the reviewer’s concern. We demonstrate that E545K mutation driven by either Nestin-cre or hGFAP-cre, result in megalencephaly, cortical and white matter dysplasia. The nature and extent of dysplasia depends on the developmental timing. We have also provided two genetic models of epilepsy caused by the E545K mutation; and we show seizure activity can be acutely suppressed by a pan-Class I PI3K inhibitor, BKM120. Moreover, we provide RPPA protein analyses which show that the protein levels are dynamically regulated by acute administration of the drug. These data conclusively show that activation of PIK3ca alone is sufficient to give rise to different developmental defects including epilepsy.

Additional specific comments: 1) The paper lacks clear evidence about the types of cells in which the mutant PIK3CA isoforms are expressed, and at which stage of development recombination occurs. This is necessary to explain whether dysregulated PIK3CA causes abnormalities in division of neural precursor cells.

We have included cre control data as Figure 1—figure supplement 2.

I wonder why the authors did not do more detailed pulse chase experiments with BrdU to study potential effects on altered proliferation of different types of precursor cells in the ventricular and subventricular zone. It would also be important to know whether proliferation of neuronal cells is differentially affected in comparison to proliferation of astrocytic precursor cells. At E16.5, the time point when the analyses shown in Figure 2 were performed, proliferation of astrocytes has already started, and the authors should do the studies shown in Figure 3 with markers that can distinguish neuronal from astrocytic precursor cells.

We have now included detailed BrdU-pulse experiments to study proliferation (1 hour pulse), cell cycle exit (1 day pulse) and birthdating early and late neurogenesis (Figure 3 and Figure 6). We have also quantitated the differential BrdU distribution in control and mutant littermates in different zones of the cortical column. We have qualitatively shown that the Pik3ca E545K mutation does not affect astrocyte shape, size or number (Figure 5—figure supplement 3). More detailed astrocyte analysis was deemed beyond the scope of the current study.

2) It is hard to explain why the cell density, as shown in Figure 3p is reduced when BrdU incorperation is increased. It is also not clear in which layers of the cortex the authors observe this reduced cell density at E16.5. To understand this phenotype, the VZ/SVZ, the mantle zone and the intermediate zone should be investigated separately.

In E16.5 Nestin-cre;E545K, multiple cellular mechanisms collectively affect the final phenotype. E16.5 E545K mutant has increased labeling index (indicating increased proliferation, Figure 3r) as well as increased cortical length (Figure 2m). The cortical density at E16.5 is not distinctly lower in any particular zone. Additionally at a later developmental time-point P0, we quantitate number of cells in different zones of the cortical column, as described in Figure 6.

Did the authors also investigate whether there is enhanced loss of cells by apoptosis or other types of cell death between E14.5 and E16.5 to explain this phenotype?

See reply to Reviewer #2’s comment 6: In Figure 3—figure supplement 1 our mutants actually show slight decreases in cell death during embryonic peak neurogenesis.

3) The phenotype with increased cell size is hard to explain. This could be due to a defect in the cell fate determination of distinct populations of neuronal types, for example when generation and survival of pyramidal cells in comparison to interneurons is enhanced, or also by altered generations of neurons in comparison to glial cells. In order to understand the phenotype of altered cortical morphology and enhanced epileptic seizures, this would be important to know.

mTOR overactivation is known to cause increased cell size (Blumcke et al., 2011; Fingar et al., 2002; Lim et al., 2015; Ljungberg et al., 2006). As we have indicated in the Discussion, in human PIK3CA brains and in cultured rodent hippocampal neurons overexpressing Pik3ca, cell size is increased, but not to the extent seen with TSC mutation, PTEN deletion, or pAKT activation.

We see no evidence of changes in cell fate (Figure 6). There is a temporal dependence on cell size, with postnatal Pik3ca activation having no effect on cell size (Figure 3—figure supplement 2). Thus, altered cell size cannot be a common basis of epilepsy in our models as both models exhibit epilepsy.

Interneurons are born at embryonic stages and their migration is almost complete before birth. Postnatal activation of Nestin-creER;E545K does not cause increased cell size or megalencephaly. The YFP-positive cells marking the cells in this model that express mutant PiK3ca do not coexpress interneuron markers like Parvalbumin and Somatostatin (data not shown). Altered interneuron development in mice where mutant Pik3ca is activated embryonically (Nestin-cre;E545K) may contribute to dysmorphology. However, this does not seem to be the common mechanism behind epilepsy since both embryonic and postnatal Pik3ca activation causes epilepsy.

4) There is a big gap between the defects in cortical thickness and the potential mechanisms that could explain the altered threshold for epileptic seizures. Is there a dysbalance between GABAergic and glutamatergic neurons and synapses in the brain of these mice? Is there defective regulation of synapse generation, function and plasticity? Are there defects in dendritic arborization and synaptogenesis? Are there differences in the morphology of astrocytes and differences in gene expression in such astrocytes, i.e. for neurotransmitter transporters, that could explain the epileptiform activity?

Although we have extensively characterized the cortical dysmorpholgy in our models, our observation that the epilepsy is acutely sensitive to treatment despite dysmorphology argues that it is an active Pik3ca-dependent process. This is a major and paradigm shifting finding. Given the extensive developmental analyses presented in addition to the epilepsy data, we consider further analysis of the synaptic physiology and the dissection of pAKT-dependent and/or pAKT-independent pathways that underlie the epilepsy to be well beyond the scope of the current manuscript; however they are the focus of ongoing studies in our lab.

5) It is not clear whether the enhanced epileptiform activity reflects a developmental defect or altered synaptic activity, which is directly driven by altered PIK3CA activation. The authors have used both a constitutive Nestin-Cre and a Tamoxifen-inducible Cre driver, but there are no data to distinguish the phenotype when E545K mutant PIK3CA is expressed from developmental stages, or only after acute induction in the adult.

While developmental defects may contribute to Pik3ca-driven epilepsy, our combined data from multiple models argue that the developmental defects are not the major drivers. Morphological differences between embryonic and postnatal E545K activation are summarized in Figure 1 and Table 1.

Other questions and points of concern: 1) In the methods section, the authors say that all mouse lines were maintained on a mixed genetic background. It is not clear what this means and whether differences in genetic background could influence the phenotype. How can the authors exclude the possibility that the more severe phenotype observed in the GFAP-Cre drivers in comparison to Nestin-Cre drivers is due to different genetic background?

We have rewritten the Materials and methods section to clarify the nature of the mixed background. Data presented in Figure 1 demonstrates that the genetic background of mice does not broadly affect Pik3ca-related phenotypes.

2) The data shown in Figure 5d are very hard to understand and not well described. What is the function of time at which the numbers of seizures occur? Does the diagram mean seizures within one minute? These bars lack standard deviations. How can one understand i.e. 0.4 seizures or 1.6 seizures per minute and why does the number of seizures fluctuate with a peak at 7 min., 15 and 22 min. after PTZ injection? Which phase of seizure activity is affected by BKM-120-treatment? Obviously, the PI3K inhibitor does not reduce seizure activity completely.

We have clarified the figure in the text and figure legend. During the 30 min after PTZ injection, mice experience several seizures. For each mouse we counted the number of seizures that they experience in one min bins to capture the complete seizure burden during our experiments. Therefore, the histogram is a representation of the average number of seizures that mice within control and mutant groups experience post-PTZ administration in 1 minute bins. These are population averages, with periodic fluctuations reflecting postictal refractory periodicity (Lado et al., 2008). Overall statistical analyses are presented in Figure 7h,i. BKM120 reduces total number of seizures, seizure severity and increases latency post-PTZ administration. BKM120 normalizes PTZ-induced seizures to untreated control (non-mutant) values.

3) The data shown in Figure 6 are hard to understand, given that the differences are generally much lower than expected, and it is also not clear which types of cells and which subpopulations of neurons are predominantly affected by altered Akt phosphorylation or other downstream signaling parameters that are expected to be altered when the PI3-K pathway is constitutively activated.

PI3K signaling is highly regulated through feedback and feed-forward loops. As we have stated in the Discussion, our proteomics data is congruent with published breast cancer data showing that even high levels PI3K pathway overactivation only causes modest changes in the levels of steady-state PI3K signaling. Our cre validation data shows cell populations predominantly affected in each mutant.

References:

R. Akbani et al., Mol Cell Proteomics 13, 1625 (2014).

T. S. Gujral et al., Oncogene 32, 3470 (2013).

B. T. Hennessy et al., Clin Proteomics 6, 129 (2010).

S. Nishizuka et al., Proc Natl Acad Sci U S A 100, 14229 (2003).

D. C. Fingar, S. Salama, C. Tsou, E. Harlow, J. Blenis, Genes Dev 16, 1472 (2002).

M. C. Ljungberg et al., Ann Neurol 60, 420 (2006).

F. A. Lado, S. L. Moshe, Epilepsia 49, 1651 (2008).

https://doi.org/10.7554/eLife.12703.026

Article and author information

Author details

  1. Achira Roy

    Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, United States
    Contribution
    AR, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article
    Competing interests
    The authors declare that no competing interests exist.
  2. Jonathan Skibo

    Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, United States
    Contribution
    JS, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article
    Competing interests
    The authors declare that no competing interests exist.
  3. Franck Kalume

    Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, United States
    Contribution
    FK, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article
    Competing interests
    The authors declare that no competing interests exist.
  4. Jing Ni

    Department of Cancer Biology, Dana Farber Cancer Institute, Boston, United States
    Contribution
    JN, Conception and design, Acquisition of data, Analysis and interpretation of data, Contributed unpublished essential data or reagents
    Competing interests
    The authors declare that no competing interests exist.
  5. Sherri Rankin

    Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, United States
    Contribution
    SR, Conception and design, Acquisition of data, Analysis and interpretation of data
    Competing interests
    The authors declare that no competing interests exist.
  6. Yiling Lu

    The University of Texas MD Anderson Cancer Center, Houston, United States
    Contribution
    YL, Acquisition of data, Analysis and interpretation of data
    Competing interests
    The authors declare that no competing interests exist.
  7. William B Dobyns

    Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, United States
    Contribution
    WBD, Conception and design, Analysis and interpretation of data, Drafting or revising the article
    Competing interests
    The authors declare that no competing interests exist.
  8. Gordon B Mills

    The University of Texas MD Anderson Cancer Center, Houston, United States
    Contribution
    GBM, Conception and design, Analysis and interpretation of data, Drafting or revising the article
    Competing interests
    The authors declare that no competing interests exist.
  9. Jean J Zhao

    Department of Cancer Biology, Dana Farber Cancer Institute, Boston, United States
    Contribution
    JJZ, Conception and design, Analysis and interpretation of data, Contributed unpublished essential data or reagents
    Competing interests
    The authors declare that no competing interests exist.
  10. Suzanne J Baker

    Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, United States
    Contribution
    SJB, Conception and design, Analysis and interpretation of data, Contributed unpublished essential data or reagents
    Competing interests
    The authors declare that no competing interests exist.
  11. Kathleen J Millen

    Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, United States
    Contribution
    KJM, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article
    For correspondence
    kathleen.millen@seattlechildrens.org
    Competing interests
    The authors declare that no competing interests exist.

Funding

Seattle Children's Hydrocephalus Research Guild (Seattle Children's Hydrocephalus Guild Seed Funds)

  • Kathleen J Millen

National Institutes of Health (R01:NS072441)

  • Kathleen J Millen

National Cancer Institute (CCSG:CA16672)

  • Gordon B Mills

Citizens United for Research in Epilepsy (SUDEP grant 2014, Christopher Donalty and Kyle Coggins Award)

  • Franck Kalume

National Institutes of Health (R01:NS058721)

  • William B Dobyns

National Institutes of Health (R01:CA188516)

  • Suzanne J Baker

National Institutes of Health (P50:CA015962-02)

  • Jean J Zhao

National Institutes of Health (P01:CA142536)

  • Jean J Zhao

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Leon Murphy (Novartis) for BKM120, Taylor Faubion for technical support, Joseph Gleeson for sharing unpublished data and Ghayda Mirzaa and Laura Jansen for discussions.

Ethics

Animal experimentation: All animal experimentation done in this study was done in accordance with the guidelines laid down by the Institutional Animal Care and Use Committees (IACUC) of Seattle Children's Research Institute, Seattle, WA (protocols 14208 and 14395), St. Jude Children's Research Hospital, Memphis, TN (protocol 278), and Dana Farber Cancer Institute, Boston, MA (protocol 06-034).

Reviewing Editor

  1. Sean J Morrison, Reviewing Editor, Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, United States

Publication history

  1. Received: October 29, 2015
  2. Accepted: November 26, 2015
  3. Accepted Manuscript published: December 3, 2015 (version 1)
  4. Version of Record published: January 27, 2016 (version 2)

Copyright

© 2015, Roy et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,910
    Page views
  • 535
    Downloads
  • 8
    Citations

Article citation count generated by polling the highest count across the following sources: Scopus, Crossref, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Human Biology and Medicine
    Laurent Perrin et al.
    Research Article
    1. Human Biology and Medicine
    2. Neuroscience
    Valentina Barrera et al.
    Research Article Updated