Gliomas are the most frequent primary tumors of the brain. Patients with grade IV gliomas (glioblastomas, GBMs) have a very unfavorable prognosis, with a mean survival of 16.6 months. This is due in large part to limitations in surgical resection and to the lack of effective treatments that could avoid the inexorable recurrence of these lethal tumors.
The comprehensive analysis of genomic and epigenomic deregulations in gliomas has shown that it is a heterogeneous disease with distinct tumor subtypes. Mutations in the Isocitrate dehydrogenase 1/2
) genes, for example, generate gliomas with a better clinical prognosis. By contrast, Epidermal growth factor receptor
) alterations have been implicated in the malignant progression of this type of cancer. EGFR
is amplified and/or mutated in nearly 50% of high-grade gliomas, favoring the survival of tumor cells and increasing their proliferative, angiogenic, and invasive capacities [1
]. Other common mutations occur in the p53 pathway, in the Rb regulatory circuit, as well as in other Tyrosine-kinase receptors or in their downstream effectors [3
]. However, even though the research has focused on the characterization of these different genetic alterations, little is known about the interaction between them.
Mutations in TP53
are a hallmark of cancer. These mutations abrogate the tumor-suppressor functions of wild-type p53, but they also endow the mutant protein with novel oncogenic activities. One of the gain-of-functions (GOFs) of mutant p53 is related to its capacity to sequester the transcription factor p63, which indirectly results in enhanced recycling of several receptors back to the plasma membrane, boosting the activation of downstream signals such as AKT. This function has been well established for several p53 mutants and different membrane receptors, including EGFR, and has even been demonstrated in GBM [4
]. Among other activities, the presence of stabilized mutant p53 isoforms result in metabolic changes through interaction with Sterol regulatory element-binding proteins (SREBP), promote interaction with DNA damage regulators on the Ataxia telangiectasia mutated (ATM) pathway, or generate resistance to DNA damage by associating with the Nuclear factor Y (NF-Y) [4
]. The detection of TP53
mutations is associated with a worse prognosis for different tumor types. In fact, several therapeutic strategies are being developed to target the stability or the function of the mutant proteins [6
]. Conversely, mutations in TP53
has been attributed to the initial steps of gliomagenesis, where they tend to co-occur with mutations in IDH1/2
, which accumulate in lower-grade gliomas (LGG) and the less aggressive GBMs [3
Consistent with the oncogenic role of EGFR in GBM, the main genetic alterations observed in these tumors are chromosomal amplifications and point mutations, which lead to hyperactivation of the receptor. The latter ones include n
-terminal deletions that relieves the EGFR dependency on extracellular ligands. Additional mechanisms contribute to increase EGFR signaling, like interaction with other receptors and amplification or overexpression of extracellular ligands [1
]. Moreover, several endocytic/recycling molecules contribute to the stabilization of EGFR in gliomas and other cancers, increasing the robustness of the signaling cascade and/or relocating the activation of the downstream targets [8
Here, we set out to study the possible association between the genetic status of TP53
in gliomas. Moreover, we investigated if mutant p53 proteins could participate in the stabilization of the receptor, which is essential for the progression of this type of tumors. Our data confirmed that gliomas expressing mutant p53 are less aggressive than the wild-type p53 tumors. Moreover, we showed that the latter accumulate alterations in EGFR
and have a greater receptor activity. Based on that, we searched for other molecules that could modulate the trafficking of membrane receptors in wild-type p53 GBMs. We focused on TMEM167A
, as we had previously linked this gene to EGFR regulation in gliomas [10
]. We measured a strong association between the expression of this gene and the worse survival of patients with wild-type p53 tumors. Moreover, we found that TMEM167A
inhibition in this subgroup of GBMs reduced the EGFR–AKT signaling axis and impaired tumor growth. This effect was rescued in the presence of mutant p53 proteins. TMEM167A
knockdown (KD) reduced acidification of the endo-lysosomal vesicles, which blocked EGFR-induced AKT activation and inhibited the autophagy processes. Moreover, treatment with bafilomycin A1 (BFA), a vacuolar ATPase inhibitor that impairs vesicular acidification, reproduced the effects of TMEM167A
downregulation in the EGFR/AKT signaling. Together, our data suggest that the increased aggressiveness of wild-type p53 gliomas is associated with higher EGFR/AKT activity, which depends on the regulation of vesicular acidification and function exerted by TMEM167A.
Detection of p53 mutations is associated with a worse prognosis in most cancers [16
]. By contrast, TP53
mutations are early events in the development of gliomagenesis [17
], and they accumulate in LGGs [7
]. However, it is not clear why tumors expressing mutant p53 proteins have a less aggressive behavior, because most of the GOF attributed to these mutations generate advantages to tumor cells: cell cycle progression, metabolic adaptation, or even increased migration [18
]. Here, we have re-evaluated how the genetic alterations in TP53
influence glioma growth and progression. We observed that alterations in EGFR
have a mutually exclusive distribution with mutations in TP53
. It is interesting to note that such negative correlation is not observed in other tumors. In lung cancer patients, for example, tumors with EGFR
mutations have a higher rate of mutant TP53
. Moreover, the presence of these p53 mutations is a negative prognostic factor [19
] and is even associated with a lower response to EGFR inhibitors in lung tumors [20
]. By contrast, the results presented here, using the in silico data and our own cohort of samples, showed that there is a higher activation of EGFR signaling in wild-type p53 gliomas. This highlights the important differences between the mechanisms of EGFR function in gliomas versus. lung cancer [21
]. Moreover, the results allow us to hypothesize that the activation of the receptor in the wild-type p53 gliomas could be responsible of the higher aggressiveness of these tumors.
One of the oncogenic activities of mutant p53 is associated with increased recycling of membrane receptors [4
]. Given the absence of such mutations in EGFR
amplified and/or mutated tumors, we searched for other molecules that could favor EGFR stability and signaling in p53 wild-type gliomas. We identified a series of vesicular transport genes that are upregulated in gliomas with alterations in EGFR
, which could have a direct implication in the functionality of this receptor. Among these genes, we picked TMEM167A
due to its higher prognostic value. Moreover, a recent screening performed in fly glioma models had allowed us to identify Kish, the Drosophila TMEM167A
orthologue, as a key modulator of EGFR trafficking/recycling during glioma development. Moreover, we had observed that the inhibition of TMEM167A
expression affects the distribution of EGFR on the endo-lysosomal system [10
]. Now, we have established that the prognostic value of TMEM167A
expression is not relevant in mutant p53 gliomas. In agreement with this, EGFR/AKT signaling was dependent on TMEM167A
, but only in wild-type p53 gliomas. AKT can be phosphorylated in response to different stimuli, especially after the activation of receptors with Tyrosine-kinase activity (RTKs) (like EGFR) or downstream of G-protein coupled receptors [23
]. Although we have previously observed that the growth of most of the lines used in this study is EGFR-dependent [12
], we cannot discard that TMEM167A might be necessary for the trafficking and/or the signaling of other receptors present in gliomas. It is also worth mentioning that the presence of mutant p53 made these gliomas independent of the EGFR–TMEM167A–AKT axis. We speculate that the alterations in the receptor’s turnover induced by mutations in p53 [4
] might modify the mechanism of EGFR/AKT activation, making glioma cells insensitive to changes in the expression and/or the function of TMEM167. Other relevant mutations for glioma development involve the loss of PTEN (phosphatase and tensin homologue deleted from chromosome 10) expression or function [3
], which activates the AKT pathway and, in particular, the production of PI (3,4)P2 [25
]. However, our results indicate that the function of TMEM167A is independent of the PTEN
status, as this gene is lost in both responsive (U87) and nonresponsive (U373) glioma cells. We could speculate that TMEM167A might function downstream of PTEN in the phosphoinositides-related signaling.
TMEM167A is part of an extensive family of proteins that are anchored in the membrane. Several members of the TMEM family have been implicated in different cancer-related processes [26
]. TMEM9, for example, has been established as a promoter of intestinal tumorigenesis by direct regulation of the v-ATPase, which favors the activation of the Wnt/-catenin pathway. The authors have described that TMEM9 binds to and facilitates assembly of the v-ATPase, being key for the maintenance of the pH in the acidic vesicles [27
]. Similar to these results, the downregulation of TMEM167A
strongly increased the pH of acidic vesicles. Moreover, BFA, which inhibits the v-ATPase function, was able to mimic the effect of TMEME167A
KD on AKT activation. Together, these results suggest that several TMEM proteins might play an oncogenic function by maintaining the proper pH of the endomembrane system and, as a consequence, favoring vesicle-mediated signaling of different receptors. Moreover, their function could be relevant to maintain the high content of acidic vesicles found in gliomas, compared with normal glial cells [10
]. Indeed, the presence of certain v-ATPase subunits has been shown to be enriched in tumor samples, where it correlated with shorter patients’ overall survival. Moreover, these authors described that BFA treatment or interference of the v-ATPase expression in GBM primary cell lines was able to inhibit the expression of stem cell markers [28
]. It is interesting to note that the endosomal effect of TMEM167A
KD was rescued in the presence of mutant p53 proteins. Although there is no GOF of p53 mutations directly linked to vesicular acidification, it is well established that there is an interplay between these mutant proteins and the autophagy and lysosomal-mediated degradation machinery [29
]. This might also explain why TMEM167A
KD did not change the Lysotracker staining and, therefore, EGFR signaling, in the presence of p53 mutations.
Deregulation of the activity of different Tyrosine-kinase receptors is of paramount importance for cancer development. Although the internalization of these receptors upon ligand binding can target them for degradation in the lysosomes, it also serves to prolong the signaling or to modulate the specific activation of different targets in different locations. In fact, deregulation of endocytosis and vesicular trafficking has oncogenic potential in different cells [8
]. One molecule that is essential for the degradation of EGFR and other receptors is RAB7, which is responsible for sorting them into late endosomes and lysosomes. In agreement with the effect observed after TMEM167A
downregulation in gliomas cells, it has been shown that RAB7 is essential for AKT activation and signaling in other cancer cells [30
]. Moreover, there is plenty of evidences supporting the existence of a tight regulation of the spatial and temporal compartmentalization of AKT activation and function [9
The most frequent EGFR mutation is the EGFRvIII isoform, an N-terminal deletion present in almost 50% of GBMs with receptor amplification [2
]. This mutation has been implicated in several aspects of the aggressiveness of gliomas, like the increase in survival/proliferation signals, or the formation of a suitable microenvironment for tumorigenesis, as well as the resistance to therapeutics [31
]. The expression of EGFRvIII has been associated with the activation of the downstream signals in the absence of ligands. In addition, it has been proposed that there is an abnormal receptor trafficking, which contributes to increased signaling [8
]. However, the data presented here indicates that the activation of AKT activation and the orthotopic tumor growth of GBM cells carrying the EGFRvIII mutation are also sensitive to TMEM167A
downregulation. It is important to emphasize the high metabolic dependence of cells expressing this oncogene, as they need to maintain high levels of autophagy to tolerate the metabolic stress [32
]. A greater autophagy flow allows the recycling of toxic products and the generation of more ATP to keep the proliferative rate. Our results suggest that TMEM167A
downregulation might alter the coordination between EGFR–AKT signaling and autophagy, which could be crucial for EGFR-dependent GBMs, even in the presence of the vIII activating mutation. Future experiments are warranted in order to characterize the relevance of vesicular acidification in EGFR signaling in the presence of other point mutations.
Overall, our results highlight the relevance of the endomembrane system regulation by TMEM167A in EGFR-dependent gliomas, because it controls a key step in the development of aggressive glioma, where EGFR signaling and autophagy maintenance converge. It would be interesting to test whether other endocytosis-related receptors, expressed in different glioma subtypes, could also be modulated by the levels of TMEM167A in a p53-dependent manner. Moreover, it would be worth testing if molecules like BFA or other v-ATPase inhibitors could have a therapeutic value in gliomas, especially in wild-type p53 tumors.
4. Materials and Methods
4.1. Human Samples
Glioma tissues samples (Table S1
) were obtained from surgeries at Hospital 12 de Octubre (Madrid, Spain), after patient’s written consent and with the approval of the Ethical Committee (Comité de Etica de la Investigación (CEI) del Hospital 12 de Octubre) (CEI 14/023). Mutations and copy number variations in TP53
, and EGFR
were identified by using a next-generation sequencing (NGS) panel (Ion Torrent technology, ThermoFisher Scientific, Waltham, MA, USA) [33
4.2. Human Glioma Cells
U87 (EGFRwt, p53wt, PTEN null) and U373 (EGFRwt, p53mut, PTEN null) cells were obtained from the ATCC. GBM2 (EGFRamp, p53mut, and PTENwt) cells were kindly donated by Rosella Galli (San Raffaele Scientific Institute, Milano, Italy). The rest of the human cells (GBM3 (EGFRwt, p53mut, and PTENwt) and GBM4 (EGFRamp/vIII, p53wt, and PTENwt) were obtained by dissociation of surgical specimens from patients treated at Hospital 12 de Octubre (Madrid, Spain). We digested fresh tissue samples enzymatically using Accumax (Merck Millipore, Burlington, MA, USA), and the cells were grown in Complete Media (CM): Neurobasal supplemented with B27 (1:50) and GlutaMAX (1:100) (ThermoFisher Scientific, Waltham, MA, USA); penicillin-streptomycin (1:100) (Lonza Group AG, Basel, Switzerland); 0.4% heparin (Sigma-Aldrich, St. Louis, MO, USA); and 40 ng/mL of EGF and 20 ng/mL of bFGF2 (Peprotech, Rocky Hill, NJ, USA).
4.3. DNA Constructs and Lentiviral/Retroviral Production
The lentiviral vectors pTRIPZ (shControl) and pTRIPZ-shTMEM167A (shTMEM167A a and b) were used to produce conditionally interfered cells. Infected cells were selected with 1 μg/mL of puromycin. Then, shRNA expression was induced by 1 μg/mL of Dox (Sigma-Aldrich, St. Louis, MO, USA) in vitro or by adding 2 mg/mL of Dox to the drinking water of the mice. The lentiviral vector to express the mutant of p53 was pLenti6/V5-p53_R273H (#Plasmid 22934, Addgene, Watertown, MA, USA). Infected cells were selected with 1 μg/mL of Blasticidin. TMEM167A-GFP vectors were used to transfected 293T cells.
To obtain the virus, the 293T cells were transiently co-transfected with 5 µg of appropriate lentivector plasmid, 5 µg of packaging plasmid pCMVdR8.74 (#Plasmid 22036, Addgene), and 2 µg of VERSUSV-G envelope protein plasmid pMD2G (#Plasmid 12259, Addgene), using Lipofectamine Plus reagent (Invitrogen, Carisbad, CA, USA). Lentiviral supernatants were prepared by transfection of 293T cells and collection of the culturing media after 48 h.
4.4. Mouse Xenografts
Animal experiments were reviewed and approved by the Research Ethics and Animal Welfare Committee at our institution (Instituto de Salud Carlos III, Madrid, Spain) (PROEX 244/14 and 02/16), in agreement with the European Union and national directives.
Orthotopic xenografts: Stereotactically guided intracranial injections in athymic nude Foxn1nu mice (Harlan Interfauna Iberica, Barcelona, Spain) were performed by administering 1 × 105 cells resuspended in 2 μL of culture medium. The injections were made into the striatum (coordinates: A-P, −0.5 mm; M-L, +2 mm; D-V, −3 mm; related to Bregma), using a Hamilton syringe, and the animals were sacrificed at the onset of symptoms.
Heterotopic xenografts: Cells (3 × 106) were resuspended 1:10 in culture media and Matrigel (Becton Dickinson, Franklin Lakes, NJ, USA) and then subcutaneously injected into athymic nude Foxn1 nu mice. The tumor volume was measured with a caliper every 7 days. Tumor volume was calculated as ½ (length × width)2.
Mice had 2 mg/mL of Dox in their drinking water to induce shRNA expression 2 weeks after the cell injection. Animals were sacrificed by cervical dislocation, and the tumors induced were removed and either fixed in 4% PFA for 24 h before IF staining or freshly frozen for RNA or protein extraction.
4.5. EGFR Signaling Assay
Cells were maintained in serum-free medium overnight. The next day, cells were stimulated with 100 ng/mL of EGF for different indicated times. Then, cells were collected and lysed for WB analysis.
4.6. Flow Cytometry
Tumor cells (U87, U373, GBM2, GBM3, and GBM4) were disaggregated with Accumax (15 min, room temperature), and then they were stained with an antibody against EGFR conjugated with FITC (Abcam, Cambridge, UK, #ab11400) diluted in PBS-1% BSA (Staining buffer) for 30 min on ice. Cells were washed in PBS, treated with propidium iodide (5 μg/mL, Sigma-Aldrich) and analyzed by flow cytometry (FACSCalibur, Bio-Rad Laboratories, Hercules, CA, USA), using the FlowJo software (https://www.flowjo.com
4.7. Western Blot Analysis
For protein expression analysis, cultured cells, human samples, or mouse tumor tissue were processed by mechanical disruption in lysis buffer (Tris–HCl pH 7.6, 1 mM EDTA, 1 mM EGTA, 1% SDS, and 1% Triton X-100), followed by heating for 15 min at 96 °C. Protein content was quantified by using a BCA Protein Assay Kit (Thermo Fisher Scientific). Approximately 30 µg of proteins were resolved by 10% or 12% SDS-PAGE, and they were then transferred to a nitrocellulose membrane (Hybond-ECL, Amersham Biosciences, Little Chalfont, UK). The membranes were blocked for 1 h at room temperature in TBS-T (10 mM Tris–HCl (pH 7.5), 100 mM NaCl, and 0.1% Tween-20) with 5% skimmed milk, and then incubated overnight at 4 °C, with the corresponding primary antibody (rabbit anti-Cathepsin B 1:1000, Santa Cruz Biotechnology, Dallas, TX, USA #sc-13989), mouse anti-GAPDH (1:1,500, Santa Cruz Biotechnology #sc-47724), rabbit anti-LC3II (1:2500, Sigma #L8919), rabbit anti-pSer473-AKT (1:1,000, Cell Signaling Technology, Danvers, MA, USA #4060), rabbit anti-AKT (1:1,000, Cell Signaling #4691), rabbit anti-pTyr1068-EGFR (1:1,000, Cell Signaling #3777), mouse anti-p62 (1:1000, Becton Dickinson #610832), and mouse anti-p53 (1:500, Santa Cruz Biotechnology #sc-126) diluted in TBS-T. After being washed 3 times with TBS-T, the membranes were incubated for 2 h at room temperature with their corresponding secondary antibody (HRP-conjugated anti-mouse (#NA931) or anti-rabbit (#NA934), Amersham Biosciences) diluted in TBS-T. Proteins were visible by enhanced chemiluminescence with ECL (Thermo Fisher Scientific), using the Amersham Imager 680 (Amersham Biosciences). Full scans of the WBs are shown in Figure S8
4.8. QRT-PCR Assay
We extracted RNA from culture cells, human samples or mouse tumor tissue by using an RNA isolation Kit (Roche, Basel, Switzerland). Total RNA (1 µg) was reverse transcribed with a Prime Script RT Reagent Kit (Takara Bio Inc, Kusatsu, Japan). Quantitative real-time PCR was performed by using the Light Cycler 1.5 (Roche) with the SYBR Premix Ex Taq (Takara). The primers used for each reaction were TMEM167A: Fw-AGTATGCTGTATAGTAATGG; Rv-ATTCAATGTTCGGAGATAA and HPRT: Fw-TGACACTGG CAAAACAATGCA; Rv-GGTCCTTTTCACCAGCAAGCT. We analyzed gene expression data by the ΔΔCt method.
4.9. Immunofluorescent Staining
The 293T cells were grown in DMEM 10% FBS over coverslips and then fixed in 4% paraformaldehyde for 20 min. Cells were blocked for 1 h in 1% FBS and 0.1% Triton X-100 in PBS and incubated overnight with the primary antibody, mouse anti-PI (3,4) P2 (1:100, # Z-P034B, Echelon Biosciences Inc (Salt Lake city, UT, USA). Anti-rabbit IgG Cy3 (1:200, Jackson Immunoresearch, West Grove, PA, USA) secondary antibodies were used, and DNA was stained with DAPI.
For the Lysotracker assay, U87 and U373 cells were grown in DMEN 10% FBS over coverslips and incubated with LysoTracker Red or LysoTracker Blue (1:500, Invitrogen) for 15 min, washed in PBS, and immediately imaging was done with Leica SP-5 confocal microscope.
4.10. Gene Expression and Survival Analyses in Silico
The expression of different genes and the follow-up overall survival data from human glioma tumors corresponding to TCGA or Rembrandt datasets were downloaded from Xena cancer Browser (https://xenabrowser.net
) and Gliovis (http://gliovis.bioinfo.cnio.es
), respectively. Kaplan–Meier survival curves were done following patient stratification, using gene expression values. The significance of the differences in overall survival between groups was calculated by using the log-rank test as Mantel–Cox (chi-square). The distribution of genetic alterations was analyzed with the TCGA datasets, using cBioportal (www.cbioportal.org
4.11. Statistical Analysis
All analyses were performed with the GraphPad Prism 5 software. The p-values < 0.05 were considered significant (*p < 0.05; **p < 0.01; *** p < 0.001; **** p < 0.0001; n.s. = nonsignificant). Error bars represent standard error of the mean. For bar graphs, the level of significance was determined by a two-tailed unpaired Student’s t-test. The difference between experimental groups was assessed by Paired t-Test and one-way ANOVA. For Kaplan–Meier survival curves, the level of significance was determined by the two-tailed log-rank test.