Glioblastoma is a universally lethal form of brain cancer that exhibits an array of pathophysiological phenotypes, many of which are mediated by interactions with the neuronal microenvironment1,2. Recent studies have shown that increases in neuronal activity have an important role in the proliferation and progression of glioblastoma3,4. Whether there is reciprocal crosstalk between glioblastoma and neurons remains poorly defined, as the mechanisms that underlie how these tumours remodel the neuronal milieu towards increased activity are unknown. Here, using a native mouse model of glioblastoma, we develop a high-throughput in vivo screening platform and discover several driver variants of PIK3CA. We show that tumours driven by these variants have divergent molecular properties that manifest in selective initiation of brain hyperexcitability and remodelling of the synaptic constituency. Furthermore, secreted members of the glypican (GPC) family are selectively expressed in these tumours, and GPC3 drives gliomagenesis and hyperexcitability. Together, our studies illustrate the importance of functionally interrogating diverse tumour phenotypes driven by individual, yet related, variants and reveal how glioblastoma alters the neuronal microenvironment.
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The RNA-seq data of tumours driven by PIK3CA variants have been deposited in the NCBI Gene Expression Omnibus (GEO) under accession number GSE123519. All other data in this article are available from the corresponding author upon reasonable request.
No custom code was used. R package limma eBayes function was used to define differentially expressed genes. Bioconductor SVA/Combat package was used for batch correction.
Venkatesh, H. S. et al. Targeting neuronal activity-regulated neuroligin-3 dependency in high-grade glioma. Nature 549, 533–537 (2017).
Venkatesh, H. S. et al. Neuronal activity promotes glioma growth through neuroligin-3 secretion. Cell 161, 803–816 (2015).
Venkatesh, H. S. et al. Electrical and synaptic integration of glioma into neural circuits. Nature 573, 539–545 (2019).
Venkataramani, V. et al. Glutamatergic synaptic input to glioma cells drives brain tumour progression. Nature 573, 532–538 (2019).
Lawrence, M. S. et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature 505, 495–501 (2014).
Samuels, Y. et al. High frequency of mutations of the PIK3CA gene in human cancers. Science 304, 554 (2004).
Chang, M. T. et al. Identifying recurrent mutations in cancer reveals widespread lineage diversity and mutational specificity. Nat. Biotechnol. 34, 155–163 (2016).
Meyerson, M., Gabriel, S. & Getz, G. Advances in understanding cancer genomes through second-generation sequencing. Nat. Rev. Genet. 11, 685–696 (2010).
Miller, M. L. et al. Pan-cancer analysis of mutation hotspots in protein domains. Cell Syst. 1, 197–209 (2015).
Ng, P. K. et al. Systematic functional annotation of somatic mutations in cancer. Cancer Cell 33, 450–462 (2018).
Vogelstein, B. et al. Cancer genome landscapes. Science 339, 1546–1558 (2013).
Zhang, Y. et al. A pan-cancer proteogenomic atlas of PI3K/AKT/mTOR pathway alterations. Cancer Cell 31, 820–832 (2017).
Brennan, C. W. et al. The somatic genomic landscape of glioblastoma. Cell 155, 462–477 (2013).
Cancer Genome Atlas Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455, 1061–1068 (2008).
John Lin, C. C. et al. Identification of diverse astrocyte populations and their malignant analogs. Nat. Neurosci. 20, 396–405 (2017).
Kfoury, N. et al. Cooperative p16 and p21 action protects female astrocytes from transformation. Acta Neuropathol. Commun. 6, 12 (2018).
Dogruluk, T. et al. Identification of variant-specific functions of PIK3CA by rapid phenotyping of rare mutations. Cancer Res. 75, 5341–5354 (2015).
Tsang, Y. H. et al. Functional annotation of rare gene aberration drivers of pancreatic cancer. Nat. Commun. 7, 10500 (2016).
Nelson, S. B. & Valakh, V. Excitatory/inhibitory balance and circuit homeostasis in autism spectrum disorders. Neuron 87, 684–698 (2015).
Ramocki, M. B. & Zoghbi, H. Y. Failure of neuronal homeostasis results in common neuropsychiatric phenotypes. Nature 455, 912–918 (2008).
Huberfeld, G. & Vecht, C. J. Seizures and gliomas—towards a single therapeutic approach. Nat. Rev. Neurol. 12, 204–216 (2016).
van Breemen, M. S., Wilms, E. B. & Vecht, C. J. Epilepsy in patients with brain tumours: epidemiology, mechanisms, and management. Lancet Neurol. 6, 421–430 (2007).
Campbell, S. L. et al. GABAergic disinhibition and impaired KCC2 cotransporter activity underlie tumor-associated epilepsy. Glia 63, 23–36 (2015).
Lang, F. M. et al. Mesenchymal stem cells as natural biofactories for exosomes carrying miR-124a in the treatment of gliomas. Neuro-oncol. 20, 380–390 (2018).
Keppler-Noreuil, K. M. et al. PIK3CA-related overgrowth spectrum (PROS): diagnostic and testing eligibility criteria, differential diagnosis, and evaluation. Am. J. Med. Genet. A. 167A, 287–295 (2015).
Mirzaa, G. et al. PIK3CA-associated developmental disorders exhibit distinct classes of mutations with variable expression and tissue distribution. JCI Insight 1, 87623 (2016).
Roy, A. et al. Mouse models of human PIK3CA-related brain overgrowth have acutely treatable epilepsy. eLife 4, e12703 (2015).
Allen, N. J. & Eroglu, C. Cell biology of astrocyte–synapse interactions. Neuron 96, 697–708 (2017).
Allen, N. J. et al. Astrocyte glypicans 4 and 6 promote formation of excitatory synapses via GluA1 AMPA receptors. Nature 486, 410–414 (2012).
de Wit, J. et al. Unbiased discovery of glypican as a receptor for LRRTM4 in regulating excitatory synapse development. Neuron 79, 696–711 (2013).
Shah, M. A., Denton, E. L., Arrowsmith, C. H., Lupien, M. & Schapira, M. A global assessment of cancer genomic alterations in epigenetic mechanisms. Epigenetics Chromatin 7, 29 (2014).
Thomas, R. K. et al. High-throughput oncogene mutation profiling in human cancer. Nat. Genet. 39, 347–351 (2007).
Zhang, J., Wu, L. Y., Zhang, X. S. & Zhang, S. Discovery of co-occurring driver pathways in cancer. BMC Bioinformatics 15, 271 (2014).
Chen, F. & LoTurco, J. A method for stable transgenesis of radial glia lineage in rat neocortex by piggyBac mediated transposition. J. Neurosci. Methods 207, 172–180 (2012).
Doench, J. G. et al. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat. Biotechnol. 34, 184–191 (2016).
Dzyubenko, E., Rozenberg, A., Hermann, D. M. & Faissner, A. Colocalization of synapse marker proteins evaluated by STED-microscopy reveals patterns of neuronal synapse distribution in vitro. J. Neurosci. Methods 273, 149–159 (2016).
Johnson, W. E., Li, C. & Rabinovic, A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8, 118–127 (2007).
Saldanha, A. J. Java Treeview—extensible visualization of microarray data. Bioinformatics 20, 3246–3248 (2004).
Buckingham, S. C. et al. Glutamate release by primary brain tumors induces epileptic activity. Nat. Med. 17, 1269–1274 (2011).
This study is dedicated to the memory of our dear friend and colleague, Kenneth L. Scott, as his intellect, enthusiasm and collaborative spirit were a driving force in this endeavour. This work was supported by grants from the Cancer Prevention Research Institute of Texas (RP150334 and RP160192 to B.D., K.L.S., C.A.M. and C.C.), National Cancer Institute-Cancer Therapeutic Discovery (U01-CA217842 to B.D., G.B.M. and K.L.S.), National Institutes of Health (R01-CA223388 to B.D. and J.L.N.; R01-NS071153 to B.D.; T32-HL902332 to K.Y.), the American Cancer Society-Rob Rutherford Glioblastoma Research Postdoctoral Fellowship (PF-15-220-01-TBG to K.Y.), and Howard Hughes Medical Institute Gilliam Fellowship (A.H.). We acknowledge the assistance of the Baylor College of Medicine Mouse Phenotyping Core with funding from the NIH (U54-HG006348). This project was supported by the BCM Small Animal MRI and Texas Children’s Hospital Small Animal Imaging Facility. Functional Proteomics RPPA Core Facility at MD Anderson Cancer Center, this facility is funded by NCI CA16672. We thank F. F. Lang for providing patient-derived cell lines under the auspices of his Internal Review Board protocol (LAB04-001) post-de-identification.
The authors declare no competing interests.
Peer review information Nature thanks Yuan Zhu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a, Whole-brain GFP fluorescence image overlaid on a brightfield image representing characteristic tumours at time of death. b, Representative bioluminescence intensity images taken at 1-month intervals starting at 2 months of age, reflective of median survival trend. Scale bar for bioluminescence intensity quantifies photon counts over the 5 min of IVIS recording. Experiments were independently repeated three times with similar results for each variant. c, Longitudinal T2 MRI of variant tumours. Readings were taken at 1-week intervals from 4 weeks of age. All images are spatially matched along the rostral–caudal axis. Red dotted outline at P42 denotes the tumour boundary. Yellow scale bar, 2.5 mm. n = 4 mice for each variant. These experiments were not independently repeated. d, BrdU (red) antibody staining on 30-day-old mouse brains. White scale bar, 40 µm. n = 4 mice for each variant. n = 18 (R88Q), 19 (C420R) and 16 (H1047R) technical repeats. e, Associated quantification for relative tumour area from MRI and BrdU incorporation analysis. Box plots are as in Fig. 3b. *P < 0.05, ***P < 0.001, one-way ANOVA. f, Left, immunofluorescence analysis of BrdU (red) incorporation on PDX tumour sections. Human tissue was identified by staining for human HLA (green). Blue scale bar, 100 μm. Right, quantification of BrdU incorporation in a 2,000 μm2 area. n = 4 mice; n = 5 technical repeats. Box plots are as in Fig. 3b. ***P < 0.001, one-way ANOVA. g, Schematic illustrating experimental approach and timeline. h, Representative image of control GFP IUE. Proliferative index was calculated by dividing the number of BrdU+ cells on the electroporated side (marked by GFP) by the number of BrdU+ cells on the non-electroporated, contralateral side. Purple scale bar, 100 μm. i, Quantification of proliferative index for activating variants C420R and H1047R along with control (GFP), demonstrating no significant difference in proliferation. n = 3 mice; n = 5 technical repeats. Box plots are as in Fig. 3b. P values were not significant (P > 0.05, one-way ANOVA).
a, Results of next-generation barcode sequencing from 2xCr tumour tissue co-electroporated with all tested alleles pooled together. Pool includes listed variants along with wild-type (WT), 4 silent mutants (E542E, E545E, T1025T and H1047H) and 18 uniquely barcoded Cherry constructs as controls. n = 3 tumours. Data are mean and s.e.m. b, Barcode sequencing for 2xCr tumours co-electroporated with the H1047R allele (tagged with barcode sequence 27), demonstrating single amplification when diluted with 50 different passenger barcodes (uniquely barcoded Cherry constructs). n = 2 tumours with 2–3 replicates; red bars denote tumour samples; grey bars denote input. Data are mean and s.e.m.
H&E staining of brains containing hypercellular and infiltrative high-grade gliomas with pleomorphic tumour cells. All tumours are histologically graded as high-grade glioma, either WHO (World Health Organization) grade III anaplastic astrocytoma or grade IV glioblastoma. Black scale bars, 1 mm; yellow scale bars, 100 μm; green scale bars, 50 μm. Representative images of each variant-driven tumour are from n = 6 brains.
Extended Data Fig. 4 PIK3CA variant differentially promote both tumour-associated and unassociated seizures.
Longitudinal EEG recordings from PIK3CA variant tumour brain (2xCr) and non-tumour brains, starting at P30. Red boxes outline interictal spike activity. Red asterisks denote generalized seizures confirmed with simultaneous videos. Traces plot from top to bottom are recordings from the left frontal, left parietal, right frontal and right parietal brain regions. Traces are representative of four mice per variant. Vertical scale bars, 300 μV; horizontal scale bars, 0.5 s.
Extended Data Fig. 5 PIK3CA variants differentially alter the local synaptic constituency at the peritumoral margins.
a, b, Immunofluorescence analysis of tumour brains, stained for excitatory (a) and inhibitory (b) synapses by the colocalization of pre- and postsynaptic markers. Analyses were focused within 200 μm of the tumour margin (dotted line), as marked by GFP (pseudo-coloured in blue). Higher magnification images from the red and blue boxes are displayed. White scale bars, 200 μm; blue scale bars, 50 μm; yellow scale bars, 12.5 μm. Experiments were independently repeated 15 times.
a, RNA-seq analysis for astrocyte-secreted factors that promote synaptogenesis. Each column represents an average of biological replicates. n = 2 (wild-type), n = 4 (C420R), and n = 3 (H1047R) mice. P values were determined by two-sided t-test on log-transformed expression values. b, RNA-seq data from the TCGA comparing the same set of genes across glioblastoma (GBM) and low-grade glioma (LGG). Asterisks denote significant difference between glioblastoma and low-grade glioma, determined by two-sided t-test on log-transformed expression values. c, Immunofluorescence analyses of P30 variant tumour brains stained for GPC3 (red) and GPF (green), demonstrating GPC3 staining at the tumour core (left) and tumour margin (right). n = 4 mice for each variant. White scale bars, 100 μm. Experiments were independently repeated four times.
a, H&E staining of 2xCr; C420R; GPC3Cr (top) and 3xCr; GPC3 (bottom) tumour brains histologically graded as high-grade glioma (either WHO grade III anaplastic astrocytoma or grade IV glioblastoma). Black scale bars, 1 mm; yellow scale bars, 100 μm; green scale bars, 50 μm. Representative images of each variant driven tumour are from n = 6 brains. b, Survival statistics for in vivo modelling of GPC3 loss and gain in various tumour models. P values were determined by log-rank test. c, SURVEYOR assay analysis of genomic DNA from 2xCr; C420R; GPC3Cr tumour tissue. Representative DNA gel electrophoresis of PCR products after SURVEYOR enzyme treatment. After the ladder (1-kb Plus, ThermoFisher, 10787018), which ranges from 100 to 1,500 bp, lanes from left to right contain on-target (ON) and top five off-target (OT1–OT5) sites with and without SURVEYOR nuclease (SN) treatment. OT3 rests in an AT-rich region and was not amplifiable. This experiment was independently repeated three times with similar results.
a, Immunofluorescence staining of 3xCr control and Gpc3 overexpression tumours for BrdU, PSD95, VGLUT1 and VGAT. White scale bar, 50 µm; blue scale bar, 5 µm. b, Quantification of BrdU immunofluorescence analysis (left) and excitatory (middle) and inhibitory (right) synapses. n = 4 (BrdU) and n = 3 (synapse) mice for each condition; n = 18 (BrdU-3xCr), n = 16 (BrdU-GPC3) and n = 15 (synapse) technical repeats for each condition and synapse type. Field for BrdU incorporation = 1,600 µm2; field for synapse analysis = 34,000 µm2. Box plots are as in Fig. 3b. *P < 0.05, **P < 0.01, ***P < 0.001, one-way ANOVA.
a, Immunofluorescence staining of co-cultures of astrocytes and neurons for PSD95, synapsin1 and MAP2 (Fig. 3b), with astrocytes overexpressing GPC3 via virus. Non-infected astrocytes were used as a control. White scale bar, 50 μm. b, Quantification of PSD95 (top) and synapsin1 (bottom) staining. n = 32 technical repeats for each condition. Data are mean and s.e.m. ***P < 0.001, one-tailed independent t-test; Tukey’s test was used to compare individual mean values. c, Representative traces of from whole-cell recording of neurons co-cultured on astrocytes virally overexpressing GFP (control) or GPC3, with associated scale bar. d, Quantification of EPSC and IPSC amplitude and frequency from co-cultures. n = 54 (GPC3, EPSC); n = 48 (control, EPSC); n = 60 (GPC3, IPSC); n = 46 (control, IPSC). Data are mean and s.e.m. ***P < 0.001, one-tailed independent t-test; Tukey’s test was used to compare individual mean values. e, Immunofluorescence staining of neuron cultures for PSD95, synapsin1 and MAP2. Wild-type astrocyte–neuron co-cultures served as a positive control. Cortical neuron cultures were grown in GPC3 condition medium (CM) or GFP control conditioned medium. White scale bar, 50 μm. f, Quantification of PSD95 and synapsin1 staining. n = 12 technical replicates for each condition. Data are mean and s.e.m. ***P < 0.001, one-tailed independent t-test; Tukey’s test was used to compare individual mean values. g, Representative traces of spontaneous postsynaptic current (SPSC) analysis of neurons co-cultured with astrocytes, GPC3 conditioned medium or GFP control medium, with associated scale bar.
PIK3CA variants found in GBM. List of all missense, silent, and in frame deletion variants of PIK3CA index on COSMIC (cancer.sanger.ac.uk/cosmic) for GBM as of 6/2019. Those alleles included in the study are in bold. Also included in the study were the non-mutated wildtype sequences (not listed) and 4 silent mutation controls (listed at the bottom).
Proliferative and synapse gene sets. List of genes and expression levels for genes associated with Fig. 2c-d.
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Yu, K., Lin, C.J., Hatcher, A. et al. PIK3CA variants selectively initiate brain hyperactivity during gliomagenesis. Nature 578, 166–171 (2020). https://doi.org/10.1038/s41586-020-1952-2
Journal of Clinical Investigation (2020)