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Biophysical insights into OR2T7: Investigation of a potential prognostic marker for glioblastoma.

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Affiliations

  • 1. Interdisciplinary Program of Genetics, Bioinformatics, and Computational Biology (GBCB), Virginia Tech, Blacksburg, Virginia.
      Authors
    • Sharp AK 1
    (1 author)
  • 2. Biomedical Sciences, Edward Via College of Osteopathic Medicine (VCOM), Blacksburg, Virginia.
      Authors
    • Newman D 2
    • Libonate G 2
    • Borns-Stern M 2
    (3 authors)
  • 3. Interdisciplinary Program of Genetics, Bioinformatics, and Computational Biology (GBCB), Virginia Tech, Blacksburg, Virginia; Department of Biochemistry, Virginia Tech, Blacksburg, Virginia.
      Authors
    • Bevan DR 3
    (1 author)
  • 4. Interdisciplinary Program of Genetics, Bioinformatics, and Computational Biology (GBCB), Virginia Tech, Blacksburg, Virginia; Department of Biochemistry, Virginia Tech, Blacksburg, Virginia; Research and Informatics, University Libraries, Virginia Tech, Blacksburg, Virginia.
      Authors
    • Brown AM 4
    (1 author)
  • 5. Biomedical Sciences, Edward Via College of Osteopathic Medicine (VCOM), Blacksburg, Virginia; Biomedical Science and Pathobiology, Virginia-Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, Virginia; Gibbs Cancer Center and Research Institute, Spartanburg, South Carolina.
      Authors
    • Anandakrishnan R 5
    (1 author)

Biophysical Journal, 10 May 2022, 121(19):3706-3718
https://doi.org/10.1016/j.bpj.2022.05.009 PMID: 35538663 PMCID: PMC9617130

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Abstract 

Glioblastoma multiforme (GBM) is the most aggressive and prevalent form of brain cancer, with an expected survival of 12-15 months following diagnosis. GBM affects the glial cells of the central nervous system, which impairs regular brain function including memory, hearing, and vision. GBM has virtually no long-term survival even with treatment, requiring novel strategies to understand disease progression. Here, we identified a somatic mutation in OR2T7, a G-protein-coupled receptor (GPCR), that correlates with reduced progression-free survival for glioblastoma (log rank p-value = 0.05), suggesting a possible role in tumor progression. The mutation, D125V, occurred in 10% of 396 glioblastoma samples in The Cancer Genome Atlas, but not in any of the 2504 DNA sequences in the 1000 Genomes Project, suggesting that the mutation may have a deleterious functional effect. In addition, transcriptome analysis showed that the p38α mitogen-activated protein kinase (MAPK), c-Fos, c-Jun, and JunB proto-oncogenes, and putative tumor suppressors RhoB and caspase-14 were underexpressed in glioblastoma samples with the D125V mutation (false discovery rate < 0.05). Molecular modeling and molecular dynamics simulations have provided preliminary structural insight and indicate a dynamic helical movement network that is influenced by the membrane-embedded, cytofacial-facing residue 125, demonstrating a possible obstruction of G-protein binding on the cytofacial exposed region. We show that the mutation impacts the "open" GPCR conformation, potentially affecting Gα-subunit binding and associated downstream activity. Overall, our findings suggest that the Val125 mutation in OR2T7 could affect glioblastoma progression by downregulating GPCR-p38 MAPK tumor-suppression pathways and impacting the biophysical characteristics of the structure that facilitates Gα-subunit binding. This study provides the theoretical basis for further experimental investigation required to confirm that the D125V mutation in OR2T7 is not a passenger mutation. With validation, the aforementioned mutation could represent an important prognostic marker and a potential therapeutic target for glioblastoma.

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Logo of biophysjGuide for AuthorsAbout this journalExplore this journalBiophysical Journal
Biophys J. 2022 Oct 4; 121(19): 3706–3718.
Published online 2022 May 10. https://doi.org/10.1016/j.bpj.2022.05.009
PMCID: PMC9617130
PMID: 35538663

Biophysical insights into OR2T7: Investigation of a potential prognostic marker for glioblastoma

Amanda K. Sharp,1 David Newman,2 Gianna Libonate,2 Mary Borns-Stern,2 David R. Bevan,1,3 Anne M. Brown,1,3,4,* and Ramu Anandakrishnan2,5,6,**
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Supplementary Materials

Abstract

Glioblastoma multiforme (GBM) is the most aggressive and prevalent form of brain cancer, with an expected survival of 12–15 months following diagnosis. GBM affects the glial cells of the central nervous system, which impairs regular brain function including memory, hearing, and vision. GBM has virtually no long-term survival even with treatment, requiring novel strategies to understand disease progression. Here, we identified a somatic mutation in OR2T7, a G-protein-coupled receptor (GPCR), that correlates with reduced progression-free survival for glioblastoma (log rank p-value = 0.05), suggesting a possible role in tumor progression. The mutation, D125V, occurred in 10% of 396 glioblastoma samples in The Cancer Genome Atlas, but not in any of the 2504 DNA sequences in the 1000 Genomes Project, suggesting that the mutation may have a deleterious functional effect. In addition, transcriptome analysis showed that the p38α mitogen-activated protein kinase (MAPK), c-Fos, c-Jun, and JunB proto-oncogenes, and putative tumor suppressors RhoB and caspase-14 were underexpressed in glioblastoma samples with the D125V mutation (false discovery rate < 0.05). Molecular modeling and molecular dynamics simulations have provided preliminary structural insight and indicate a dynamic helical movement network that is influenced by the membrane-embedded, cytofacial-facing residue 125, demonstrating a possible obstruction of G-protein binding on the cytofacial exposed region. We show that the mutation impacts the “open” GPCR conformation, potentially affecting Gα-subunit binding and associated downstream activity. Overall, our findings suggest that the Val125 mutation in OR2T7 could affect glioblastoma progression by downregulating GPCR-p38 MAPK tumor-suppression pathways and impacting the biophysical characteristics of the structure that facilitates Gα-subunit binding. This study provides the theoretical basis for further experimental investigation required to confirm that the D125V mutation in OR2T7 is not a passenger mutation. With validation, the aforementioned mutation could represent an important prognostic marker and a potential therapeutic target for glioblastoma.

Significance

Glioblastoma multiforme (GBM) is an aggressive malignant disease with less than 5% five-year survival rate even with treatment. Identifying novel therapeutic targets is essential, since current treatment options have a limited effect on patient survival and inadequate efficacy in inhibiting disease progression. Identification of novel targets specific to GBM and the exploration into their biophysical characteristics and dynamic structures can help aid in overcoming limitations of current treatment options and provide a better understanding of GBM pathophysiology.

Introduction

Glioblastoma multiforme (GBM) is an aggressive and highly drug-resistant form of brain cancer. GBM is the most common central nervous system malignant tumor, accounting for 48.3% all brain cancers (1). GMB has an incidence rate of 3.19 per 100,000 people and is considered incurable (2,3). Less than 5% of GBM patients survive beyond five years with treatment and as few as three months without treatment (4,5). Treatment options for GBM have limitations as evident from the length of patient survival and rapid progression of the disease, partly due to inadequate knowledge of its pathophysiology (6,7). Common treatments consist of surgical resection, radiation, and chemotherapy. However, due to lack of early symptoms and resulting invasiveness, full remission is rarely achieved (8). These different treatment methods have shown no differences in preventing GBM recurrence, demonstrating that current therapy options do not alter disease progression (9). With GBM displaying rapid disease progression and low survival rates, there is an urgent need for better therapeutic strategies.

Novel GBM specific targets for therapeutic development are needed to increase survival and further understand disease pathophysiology. Current GBM research has been exploring immunotherapy treatments, such as peptide-targeted vaccines (10), but still requires further understanding of the biological mechanism of disease. Although several prognostic markers and therapeutic targets are under investigation and show promise, such as epidermal growth factor receptor mutation and expression, O6-methylguanine DNA methyltransferase promoter methylation, and isocitrate dehydrogenase mutations (IDH1/2), many have yet to demonstrate clinical efficacy in GBM (11) and exhibit limitations because of the need to cross the blood-brain barrier (12). Further understanding into the functional pathways associated with GBM progression can help identify novel targets and more effective therapeutics.

Bioinformatics and big data investigative work can help aid in the discovery of genetic mutations involved in disease progression, identification of new potential druggable targets, and conducting in-depth analysis into potential prognostic markers. Here, we identified a mutation in the olfactory receptor family 2 subfamily T member 7 (OR2T7) that occurred frequently in GBM samples. The D125V mutation occurred in 10% of 396 GBM samples in “controlled” sequencing data from The Cancer Genome Atlas (TCGA) (13). However, it does not occur in any of the 2504 sequences in the 1000 Genomes Project (14), suggesting that the mutation may have a deleterious effect on cellular function. OR2T7 contains modified MAYDRYVAIC and PMLNPFIY motifs and two conserved olfactory receptor (OR) motifs, and has been classified as an OR based on its sequence similarity (15), although OR2T7 has not been individually studied previously.

ORs are a subclass of class A (rhodopsin-like) G-protein-coupled receptors (GPCRs) involved in transmembrane signal transduction. GPCRs have been implicated in both tumor proliferation (16, 17, 18, 19, 20) and suppression (21,22). Although ORs are primarily expressed in the olfactory epithelium, ectopically expressed ORs have also been implicated in several cancers (23, 24, 25, 26, 27, 28). For example, OR51E2, OR1A2, and OR51B4 inhibited cell proliferation and increased p38 mitogen-activated protein kinase (MAPK) phosphorylation (activation) in prostate cancer cells (29), hepatocarcinoma cells (30), and colorectal cancer cells (31), respectively. OR2J3 and OR2T6 induced apoptosis and inhibited cell proliferation via the extracellular signal-regulated kinase pathway in non-small-cell lung cancer (32) and breast cancer (33), respectively. OR2AT4 and OR51B5 reduced cell proliferation and reduced p38 MAPK activation in myelogenous leukemia (34,35). While it is understood that ORs may play a role in various cancers, how OR2T7 impacts GBM is unknown, and it is necessary to explore its structure-function relationship to understand its possible effect on disease progression.

The goal of this study is to investigate the functional effect of the newly identified OR2T7 D125V mutation and its potential role in the progression of GBM coupling experimental, bioinformatics, and computational techniques (Fig. 1 a). Quantitative polymerase chain reaction (qPCR) was used to confirm that OR2T7 is expressed in a GBM cell line, U87MG (29). Kaplan-Meier analysis showed that the mutation may affect progression-free survival. Analysis of DNA and RNA sequencing data was used to identify differentially expressed genes in GBM samples with the D125V mutation. In silico strategies, including molecular modeling and molecular dynamics (MD) simulations, were used to explore the impact of the D125V mutation on the overall protein structure-function and biophysical properties of OR2T7 (Fig. 1 b). The findings from structural investigations suggest that the D125V mutation impacts helical dynamics and the subsequent Gα-subunit binding to OR2T7, possibly affecting the progression of GBM via the p38 MAPK tumor-suppressor pathway.

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OR2T7 and the mutation D125V present as a potential novel prognostic marker in glioblastoma. (a) Coupled computational and experimental workflow for investigating the novel prognostic marker, OR2T7. (b) Visualization of OR2T7 WT homology model with domain names and location of D125V mutation. To see this figure in color, go online.

Materials and methods

Glioblastoma tumor sample sequencing data

TCGA contains mutation data from DNA sequencing for 396 tumor samples from glioblastoma patients (5). Mutation data were available from the TCGA repository in mutation annotation format (MAF) for download, with approval for controlled data access. For this study we used variants called using the Mutect2 protocol (36). RNA sequencing data, with fragments per kilobase of transcript per million mapped reads (FPKM) values, was available for 387 of these tumor samples. This open-access RNA sequencing data was also downloaded from TCGA repository.

Differential gene expression calculation

Differential gene expression statistics were calculated using FPKM values calculated from RNA sequencing data. The two-sided t-test in the Python statsmodels.stats.weightstats.ttest_ind module was used to calculate p-values. The Benjamini-Hochberg correction for multiple testing in the Python statsmodels.stats.multitest.fdrcorrection module, with error rate α = 0.05, was used to calculate false discovery rate (FDR).

Glioblastoma patient survival data

TCGA patient survival data are open access and were downloaded from cBioportal, along with Kaplan-Meier survival statistics and log rank p-value (37).

Glioblastoma cell line culture

The glioblastoma cell line U-87 MG was obtained from the American Type Culture Collection. Cells were cultured in Gibco (Waltham, MA) Dulbecco’s modified Eagle’s medium with 10% fetal bovine serum and passaged every 3–4 days in accordance with the protocol described in the product documentation.

Quantitative polymerase chain reaction

Total RNA was extracted from cell culture after passage #6 using the Qiagen (Hilden, Germany) RNeasy Mini kit and the recommended protocol from the product manual. RNA was reverse transcribed to cDNA using the Applied Biosystems (Waltham, MA) High Capacity cDNA Reverse Transcription Kit with RNase Inhibitor and the recommended protocol from the product manual. qPCR was performed on the QuantStudio 3 Real-Time PCR system (Thermo Fisher, Waltham, MA) using the Applied Biosystems PowerUp SYBR Green Master Mix and the recommended protocol from the product manual.

Homology modeling

The Basic Local Alignment Search Tool (BLAST) (38) was utilized to determine structures with solved structures similar to OR2T7 (accession: P0C7T2), which identified the structure of adenosine receptor A2a (PDB: 3PWH) (39) sharing 28% similarity and 15% identity to OR2T7 based on sequence alignments performed in Schrödinger-Maestro v. 2020.3 (40). MODELLER 9.22 (41) was employed to build the homology models of the wild-type (WT) and D125V mutant using an adenosine A2a template (39). Structural validation of each model was analyzed using Ramachandran plots (42), QMEAN (42), ProSA (43), and Verify3D (44). Each structure displayed similarities to the template structure.

Molecular dynamics simulations: System construction and simulation

The CHARMM-GUI membrane builder (45) was used to prepare the OR2T7 homology models of WT and D125V structures in a membrane environment. The exofacial membrane contained 176 cholesterol, 64 1-palmitoyl-2-oleoyl-sn-phosphatidylcholine, and 132 palmitoylsphingomyelin molecules while the cytofacial membrane was built with 156 cholesterol, 32 1-palmitoyl-2-oleoyl-sn-phosphatidylethanolamine, 64 stearoyl-oleoyl-phosphatidylserine, and 108 1-stearoyl-2-docosahexaenoyl-sn-glycerophosphoethanolamine molecules, based on literature (46). The systems were solvated with 0.15 M KCl and TIP3P water models. Output structures were simulated using GROMACS v. 2019.3 software (47) using the CHARMM36m force field (48). Energy minimization used the steepest descent integrator method. Equilibration was performed in a six-step process at 310 K and 1 bar with the integrator MD algorithm. Four replicates were produced at the first step utilizing the Berendsen thermostat temperature coupling method with random velocities applied (49). The second step continued the same parameters as the first step. The third step applied the Berendsen thermostat temperature coupling method with a semi-isotropic coupling type (49). The last three steps continued the same parameters as the third step with a slow release of position restraints on the protein-membrane system. MD production was run at 310 K and 1 bar and applied the Verlet cutoff scheme for neighbor searching, the Nosé-Hoover temperature-coupling algorithm (50,51), linear constraint solver constraint algorithm (52), the fast smooth particle-mesh Ewald electrostatics Coulomb type (53,54), and cutoff with force-switch modifier Van der Waals interactions. Following equilibration, restraints were removed, and each system was simulated for a total of 1000 ns. Additional parameter files, starting structures, and cluster structures related to this work can be found on our public Open Science Framework page (https://osf.io/82n73/).

Molecular dynamics simulation analysis

Analysis was performed on both WT and Val125 mutant MD simulations using GROMACS (47) analysis suite and in-house scripts. Analysis time frame (last 250 ns) of simulated structures was based on root-mean-square-deviation (RMSD) calculations and determination of system stability using structural clustering and secondary structure analysis (Fig. S4). Clustering of dominant morphologies was performed on the last 250 ns on full structure and structure without exocellular loops (Fig. S5 and Table S1) as well as time-series clusters every 100 ns (Figs. S13 and S14; Tables S2 and S3), with a cutoff of 0.2 nm. Distance matrices to determine the smallest distance between residue pairs were analyzed with the GROMACS mdmat option for the start and the last 250 ns of simulation time (Figs. S6–S8). z-Axis distance calculations were performed using the distance option in GROMACS between each residue in TM6 and the center of mass of the membrane (Fig. S9). Covariance and principal component analysis (PCA) was performed using GROMACS covar and anaeig options (Fig. S10). DSSP analysis in GROMACS was used for secondary structure analysis (Figs. S11 and S12). Local secondary structure impacts of D125V used residues 122–128. Minimum distance analysis performed using mindist option in GROMACS used residues 235–240 for TM6 and residue 294 for the TM7 hinge, then residues 122–128 for ICL-2 and 217–226 for ICL-3. To calculate the angle bend within TM6 helix, vector 1 used the Cα atoms of residues 235 and 248 and vector 2 used the Cα atoms of residues 248 and 258 (Fig. S15). For the angle bend between TM6 and TM7, vector 1 used the Cα atoms of residues 235 and 248 and vector 2 used the Cα atoms of residues 292 and 297 (Fig. S15). To analyze the angle bend in adenosine A2a, we utilized an “open” structure (PDB: 6GDG) and “closed” structure (PDB: 3PWH) from the PDB to calculate the angle bend with TM6 using the Cα atoms of residues 241 and 255 for vector 1 and residues 226 and 241 for vector 2. For the angle between TM6 and TM7 in adenosine A2a, the Cα atoms of residues 226 and 241 were utilized for vector 1 and residues 290 and 294 for vector 2. Structures were visualized using PyMOL v. 2.4.0 (55). In-house analysis scripts and starting simulation structure and topology data can be found on our public Open Science Framework page (https://osf.io/82n73/).

Results and discussion

Coupled computational and experimental strategies show that 1) the D125V mutation occurred frequently in TCGA glioblastoma samples, 2) OR2T7 is expressed in a glioblastoma cell line, 3) patients with this mutation have shorter survival expectancy, 4) p38 MAPK pathway genes, including proto-oncogenes and putative tumor-suppressor genes, are underexpressed in glioblastoma samples with the mutation, 5) the mutation Val125 impacts the Gα-binding domain, and 6) this is likely to structurally influence the “open” and “closed” conformational morphology.

The Val125 mutation in OR2T7 affects the expression of p38 MAPK pathway genes in glioblastoma

Controlled DNA sequencing data for 396 glioblastoma tumor samples in TCGA were analyzed to quantify the distribution of variants. These samples contained moderate and high-impact (protein-altering) variants in 32,121 different genes. Moderate variants included missense mutations and in-frame indels. High-impact variants included frameshift indels, nonsense mutations, and splice site variants. Note that many of these variants, including all of the variants in OR2T7, are only identified in controlled access TCGA data to prevent donor de-identification (30). Therefore variants, such as those in OR2T7, are not accessible from public websites such as cBioPortal, which are based on open-access data. Of the 396 glioblastoma samples, 105 samples had 27 distinct variants in OR2T7 (Fig. 2 a). The C111Y (SNP: rs61834488) and D125V (SNP: rs1782240) variants occurred in 55 (14%) and 40 (10%) of the 396 samples, respectively. All of the other 25 variants occurred in 1% or less of the samples. The C111Y mutation also occurred in 10% of sequences in the 1000 Genomes Project (14), suggesting that this mutation occurs frequently in the general population and is unlikely to have a significant negative effect. On the other hand, Val125 did not occur in any of the 1000 Genome Project sequences, suggesting that this mutation is likely to have a deleterious effect on cellular function. Therefore, we investigated the D125V mutation in further detail to determine whether and how it may affect the progression of glioblastoma.

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D125V mutation in OR2T7 affects expression of p38 MAPK pathway genes. (a) Occurrence of OR2T7 mutations in N = 396 glioblastoma samples from The Cancer Genome Atlas. (b) OR2T7 expression measured by qPCR. GAPDH is positive control and No DNA the negative control. For clarity, change in normalized reporter value (ΔRn) > 0.5 is not shown. (c–e) (c) Overall, (d) disease-specific, and (e) progression-free survival for glioblastoma patients with and without the D125V mutation. N = 40 samples with D125 and N = 347 excluding D125V. (f) Differential gene expression. Fold change = FPKM for samples with the D125 mutation/FPKM for samples without the mutation. For clarity, log10p-values >5 are not shown. (g) Distribution of FPKM values for samples with and without the D125V mutation for the five genes discussed in further detail. *FDR = 0.05, **FDR < 0.002. +For clarity, FPKM for Casp14 and p38α is scaled up by 10,000× and 10×, respectively. For (f) and (g), N = 17 samples with D125V and N = 118 excluding D125V. To see this figure in color, go online.

We first confirmed that the OR2T7 gene is expressed (transcribed) in glioblastoma cells. We cultured U87MG, a glioblastoma cell line (29), isolated RNA, reverse transcribed the RNA to complementary DNA (cDNA), and amplified a segment of OR2T7 mRNA sequence using qPCR to show that the gene is expressed in this cell line (Fig. 2 b).

Clinical data associated with the glioblastoma samples were analyzed to determine whether the D125V mutation may affect patient survival. Kaplan-Meier analysis showed that overall survival was correlated with the Val125 mutation (Fig. 2 c, log rank p-value = 0.14) and more strongly correlated with disease-specific and progression-free survival (Fig. 2 d and e, log rank p-value = 0.08 and 0.05, respectively). Median progression-free survival was 4.7 months for patients with the mutation compared with 7.2 months for patients without the mutation.

Gene expression data showed that 153 genes were underexpressed in samples with the mutation compared with those without the mutation (Fig. 2 f, FDR ≤ 0.05). See Table S1 for the expression levels of all genes in all samples. These underexpressed genes included several genes in p38 MAPK pathways: JunB, caspase-14 (Casp14), c-Fos, c-Jun, p38α MAPK, and Ras homology member B (RhoB) (Fig. 2 g, FDR = 0.0002, 0.0008, 0.0008, 0.0017, 0.0513, and 0.0523, respectively). p38α is the most abundant of four p38 MAPK isoforms (31). Several GPCRs, including the proteinase-activated receptor (PAR-1), muscarinic 1 acetylcholine receptor (M1), and α-1B adrenergic receptor (ADRA1B), have been shown to activate p38 MAPK pathways (32, 33, 34, 35,56). c-Fos, c-Jun, and JunB are subunits in the transcription factor activating protein (AP-1), which is a heterodimer or homodimer consisting of subunits from the family of Fos and/or Jun family of proto-oncogenes. The expression of these AP-1 subunits is regulated by different mechanisms, including p38 MAPK pathways. Activated p38 MAPK targets transcription factors for these genes to their transcription promoter sites (32,33,57, 58, 59). In addition, the expressions of c-Fos, c-Jun, and JunB have been extensively implicated in the progression of gliomas (60, 61, 62, 63, 64). p38 MAPK also targets Casp14 and RhoB transcription factors, which include c-Jun and JunB, to their promoter sites (65, 66, 67, 68, 69). Casp14 and RhoB have also been shown to suppress tumor growth (67,69, 70, 71, 72, 73, 74, 75, 76), although in some cases they have been associated with promoting tumor growth (77, 78, 79). In the discussion below, we describe possible pathways that could explain the differential expression of these genes in glioblastoma samples with the OR2T7 Val125 mutation.

The WT and Val125 mutant display structural differences in the Gα-binding domain

Homology models of the WT OR2T7 and D125V mutant OR2T7 were constructed using MODELLER v. 9.22 with adenosine receptor A2a (PDB: 3PWH) (39) as a template. OR2T7 WT and Val125 sequences displayed 28% identity and 15% similarity to the adenosine receptor A2a template structure (Fig. S1). While sequence identity was low to the homology model template, GPCRs follow a highly conserved 7-transmembrane structural moiety and can be further refined using MD simulations (36,80). The constructed homology models were validated using Ramachandran plots (37), ProSA (43), Swiss-Model Local Quality Estimate (37), and Verify3D (44) to analyze backbone angles, side-chain positioning, and structural statistics against solved protein structures (Figs. S2 and S3). These metrics demonstrated sufficient model quality for the constructed homology models and value in utilizing them for further computational experiments.

Systems were built for MD simulations using the OR2T7 WT and Val125 mutant homology models with the CHARMM-36m force field (48) and GROMACS software (47). Systems were simulated for 1 μs with four replicates for each system, for a total of 8 μs sampling time. To determine overall system convergence for the simulated systems, we analyzed RMSD and RMSD clustering over a sampling of the last 250 ns (Fig. S4). Dominant morphologies from simulation displayed overall well-preserved helical structure in both OR2T7 WT and Val125 simulations, with variation in the position and tilts of transmembrane domain 6 (TM6) helix observed in the WT OR2T7 structures (Fig. S5 and Table S1).

To examine global changes impacted by the Val125 mutation, we first investigated overall compactness of the system. Radius of gyration (Rg) demonstrates that the Val125 structure has less overall variation in system compactness compared with the WT (Fig. 3 a), although the average WT compactness is similar to the Val125 mutant structure (2.29 ± 0.04 nm and 2.28 ± 0.02 nm, respectively). To determine whether the compactness variation differences impacted overall structural interactions, we explored the overall distance variation in the structures by examining minimum distances between residue pairs (Figs. 3 b and S6–S8). This analysis suggests that there were differences between the WT and 125V structures within the extracellular loop region, TM3 and TM5 helices, TM2 and TM6 helices, and TM1 and TM7 helices. Additionally, the Val125 residue was further away from TM4 and the loop between TM5 and TM6 compared with the WT Asp125 position. Analysis of the position of the TM6 domain in the z-axis relative to the membrane center of mass showed that TM6 in the mutant structure was measurably higher in the membrane compared with WT (Figs. 3 c, ​,44 b, and S9). TM6 and TM7 have been shown to play a role in Gα-subunit binding and linked “open” and “closed” conformations in other GPCRs including adenosine A2a (Fig. 4 c) (39,81). This position shift within the membrane may allow for movement in the TM helices in the WT structure, allowing more flexibility to move between “open” and “closed” conformations. This change in structural positioning within the membrane suggests an increase in overall compactness within the Val125 mutant by decreasing overall structural flexibility.

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Global changes impacted from the Val125 mutation. (a) Averaged radius of gyration of OR2T7 WT (teal) and D125V (tan) structures with shaded standard deviation over time. (b) Averaged residue pair distance matrix differences between the WT and mutant systems. Distance calculations were made using GROMACS mdmat function over the last 250 ns. Red displays residues closer in WT system, and blue displays residues closer in D125V system. (c) TM6 helix z-coordinate positioning in membrane, with blue showing the position of WT and red showing the position of D125V. Black threshold lines indicate approximate positioning of membrane. To see this figure in color, go online.

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OR2T7 mutant displays structural morphology differences from WT. (a) Principal component analysis of the projections of WT (teal) and D125V (tan) systems. (b) Membrane visualizations of WT (teal) and D125V (tan). (c) Structural overlays of WT (teal) of adenosine A2a (gray) in open conformation (PDB: 6GDG) and closed conformation (PDB: 3PWH). (d) Extreme position projections of the average structure of MD simulation trajectories. WT (teal) and D125V (tan), with arrows displaying the vectors from the two extreme trajectories (gray) performed using modevector in PyMOL. To see this figure in color, go online.

To further explore the impacts of global movements in the WT and Val125 mutant systems, we explored aggregate conformational ensemble differences between the WT and Val125 OR2T7 structures using covariance and PCA on the mass-weighted coordinates of the systems (Fig. S10). The overall structure showed that the WT and Val125 mutant structures sampled similar phase space, which is expected with only a single mutation site. Additionally, we examined the aggregate conformational differences within the TM5, TM6, and TM7 helices because of their involvement in “open” and “closed” conformations (Fig. 4 a). The WT and D125V systems displayed different phase space occupation with some overlap, providing insight that each system occupies additional space not sampled in the other. The extreme positions from individual PCA show that WT OR2T7 encompasses most of the movement in all three TM helices while Val125 OR2T7 displays movement mostly located in the TM7 domain (Fig. 4 d). Analysis of residues that are most significantly different in the covariance matrix employing DIRECT-ID (82) showed that the TM5 and TM6 cytofacial domains contained the largest variations in conformational movement between the WT and mutant systems, specifically Ser220, Glu221, Ala222, Ala228, Val229, Ala230, Thr231, Cys232, and Ser233.

Structural investigation into the local disturbances at the 125 position revealed that the Val125 mutation influenced structural stability of the α-helix between the TM3 and TM4 domains (Fig. 5 a). Secondary structure analysis showed that the Val125 mutant OR2T7 simulations displayed a loss of α-helical structure and less consistency in positioning compared with the WT (WT α-helical percentage: 53.81% ± 6.34%, Val125 α-helical percentage: 37.31% ± 8.02%; Fig. 5 b), even though valine and aspartate have similar propensities to stabilize α-helix formation (83). The observations in helical differences were not observed in the overall structure of either system (Figs. S11 and S12), demonstrating that the differences in secondary structure are only local to the one domain.

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OR2T7 D125V mutation alters the secondary structure of local helix, impacting global structural changes. (a) Visualization of residue 125 position located on OR2T7 ICL-2 domain pre- and post-MD simulation by replicate. Post-MD cluster replicates 1–4 are shown as dark teal to light teal in WT and dark tan to light tan in D125V. (b) Secondary structure percentages of helix between residues 122 and 128. (c) Averaged minimum distance between TM6 and TM7 domains of WT and Val125 with standard deviation shaded. WT is shown in teal and Val125 in tan. (d) Domains of interest on OR2T7 used in minimum distance calculations. To see this figure in color, go online.

Time-series cluster analysis demonstrated that the WT system displays fluctuation in the TM6 domain while the D125V system appeared more consistent in positioning Figs. S13 and S14; Tables S2 and S3). Investigation into the distance between TM6 and TM7 showed that WT has more variation in the distance between these two helices while D125V stays relatively consistent over time (Fig. 5 c and d), indicating that the interactions between the TM6 and TM7 of the D125V structure could be more favorable. Some GPCRs require a bend in the TM6 helix to allow for an “open” conformation (81,84). For inspection into OR2T7 “open” conformational position or TM6 helix bending, the angles within the TM6 helix and angles between the TM6 and TM7 helices were analyzed over the whole simulation (Fig. 6). The angles within the TM6 helix showed that the WT system started with a large bend in the TM6 helix but eventually stabilized to a similar, yet slightly smaller, angle as compared with the D125V mutant (Fig. 6 a). The distribution of the angles shows that both systems displayed a unimodal distribution (Fig. 6 a). Analysis of the angle between the TM6 and TM7 helices showed that this angle in the WT system was larger than that of the Val125 mutant system (Fig. 6 b). The distribution of the angles between the TM6 and TM7 helices showed a trimodal distribution for both systems, but inconsistent and only partial overlap of distribution for the angles between WT and Val125 structures (Figs. 6 b and S15), indicating that the angles between the TM6 and TM7 helices are measurably different from each other and present different mean angle values (Fig. S16). Comparing the WT conformational ensembles through simulation with the adenosine A2a experimentally solved structures, we observed that the TM6 helix bend is comparable with the experimentally determined “open” and “closed” conformations (Fig. 4 c). In the “open” and “closed” structures for adenosine A2a, the angles within the TM6 helix were 132.2° and 144.1° and the angles between TM6 and TM7 helices were 61.0° and 46.0°, respectively, demonstrating that the wider-angle bend within TM6 and smaller angle between TM6 and TM7 displays a “closed” conformation.

An external file that holds a picture, illustration, etc. Object name is gr6.jpg

OR2T7 mutant displays differences in “open” and “closed” conformations. (a) Angle bend within the TM6 helix over time and histogram distribution of angles. (b) Angle bend between the TM6 and TM7 helices over time and histogram distribution of angles. (c) Difference between “open” and “closed” positions in WT systems. To see this figure in color, go online.

To explain how conformational morphology is impacted by the D125V mutation, we explored the minimum distances between residue pairs. In this analysis we observed that WT 125-residue position was closer to the intracellular loop-3 (ICL-3) compared with the mutant (Fig. 3 b). To further explore the impact of the mutation on the ICL-3 domain, we analyzed the hydrogen-bonding interactions between residues surrounding position 125 with residues on ICL-3 and the lower TM5 domain (Fig. S17). The hydrogen-bond interaction network appears to be shifted from 226–229 with 117–119 in WT to 234–235 and 115–120 in the mutant (Figs. S17 and S18), displaying a relationship between movement in TM6 and residue 125. The interplay of residue interactions and hydrogen-bond network shift explains the biophysical characteristic differences between the WT and mutant OR2T7 structural morphologies and that the interaction between the 125 position and the ICL-3 impacts the bend in TM6, facilitating an “open” or “closed” conformational ensemble.

Conclusions

There is an urgent need to identify novel GBM prognostic markers and drug targets due to the low five-year survival rate, aggressive disease progression, and limited success with current therapeutic options. Our results show that the D125V mutation in OR2T7 is likely to downregulate its GPCR signal transduction activity (Fig. 2) by reducing the expression of c-Fos, c-Jun, JunB, p38α, Casp14, and RhoB (Fig. 2 g), and adversely affect survival of glioblastoma patients (Fig. 2 c–e). We hypothesize OR2T7 GPCR-p38 MAPK pathways that could explain these findings. The hypothetical OR2T7 GPCR-p38 MAPK pathways include the five stages illustrated in Fig. 7 b. 1) The OR2T7 GPCR is activated by an agonist (activating ligand). For example, the olfactory receptor agonists monoterpene, troenan, β-ionone, and sandalore have been shown to activate OR1A2 (30), OR51B4 (31), OR51E2 (29), and OR2AT4 (32), respectively, and inhibit tumor growth (16, 17, 18, 19,21,22,85, 86, 87, 88, 89, 90). 2) Activation of OR2T7 catalyzes the G-protein-bound GDP to GTP exchange and the release of the Gα (91). 3) Released GTP-bound Gα triggers a p38 MAPK cascade. 4) Activated p38α promotes the expression of c-Fos, c-Jun, JunB, RhoB, and Casp14 genes. Transcription factor TCF is targeted to the c-Fos promoter site by activated p38α to promote c-Fos (57). Activating transcription factor 2 (ATF2) and AP-1 subunits c-Jun and JunB are targeted to the c-Jun and JunB promoter site by p38α to promote transcription of c-Jun and JunB (32,58). E1A-associated cellular P300 transcription factor and c-Jun are targeted to the RhoB promoter site by p38α to promote RhoB (65, 66, 67), and JunB and c-Jun are targeted to the Casp14 promoter site by p38α to promote Casp14 transcription. 5) This promotes the expression of putative tumor suppressors RhoB and Casp14 (67,69, 70, 71, 72, 73, 74, 75). The hypothesized pathway illustrated in Fig. 7 could explain our experimental findings.

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GPCR-p38 MAPK pathways that could explain our findings. (a) Overlay of WT OR2T7 open and closed positions from simulation and Gα from adenosine receptor A2a (PDB: 6GDG) demonstrating Gα accommodation. (b) 1) OR2T7 is activated by agonist (Ag) binding. 2) OR2T7 activation catalyzes GDP to GTP exchange and the release of the Gα subunit of the G-protein complex. 3) Gα triggers p38α MAPK pathways. 4) p38 targets promoters to c-Fos, c-Jun, JunB, RhoB, and Casp14 promoter sites. 5) Expression of RhoB and Casp14 suppresses tumor growth. To see this figure in color, go online.

In addition to the described pathway, many of the details of the complex GPCR-p38 MAPK pathway remain to be fully understood, and the specific pathway activated by each GPCR depends on its activating ligand and G-protein specificity (78,91,92). The studies noted above together with our findings support the hypothesis that activation of OR2T7 could promote the expression of RhoB and Casp14 via the p38 MAPK pathways and, conversely, the Val125 mutation in OR2T7 could downregulate the expression of putative tumor suppressors RhoB and Casp14 by impacting Gα-subunit binding (Figs. 7 b and S19), adversely affecting glioblastoma patient survival (Fig. 2 c–e). Three other olfactory receptors, OR51E2, OR1A2, and OR51B4, when activated by their respective agonists β-ionone, troenan, and monoterpene, have been shown to induce apoptosis, inhibit cell proliferation, and increase p38 MAPK activation in prostate cancer cells (29), hepatocarcinoma cells (30), and colorectal cancer cells (31), respectively, lending further support to our hypothesis.

To explain the structural and biophysical impacts of D125V that may influence the downregulation of the GPCR-p38 MAPK pathway, we explored the structural dynamics of OR2T7 WT and Val125 mutant by using MD simulations. Exploration of conformational ensembles of the WT and mutant systems demonstrates that, while the mutation does not disturb overall structural integrity (Fig. S10), WT OR2T7 had more dynamic fluidity and variation in structural compactness that is likely influenced by helical positioning within the membrane (Fig. 3 c). The mutation from aspartate to valine at position 125 causes local structural disturbances by destabilizing the helix between TM3 and TM4 domains, as demonstrated in secondary structure analysis, and is likely impacted by polarity changes (Fig. 5 a and b). These biophysical changes have facilitated global structural impact observed in the interactions between residue pairs and conformational ensembles (Fig. 4 b and d), displaying distinct differences between the OR2T7 WT and Val125 mutant structures most notably in the TM6 and TM7 domains.

GPCRs follow a universal mechanism utilizing TM6 as a “macroswitch” and require TM5 and TM7 for structural stabilization (84). In class A, or rhodopsin-like GPCRs, the rotation of TM6 is required for G-protein coupling and structural activation (84). TM6 and TM7 are important domains for facilitating Gα-subunit binding and has been shown in other GPCRs that an “open” conformation, where TM6 forms a bend away from TM7, is required for structural activation and G-protein accommodation (81). Simulation results indicate morphological differences within the TM6 domain and that the sampling of “open” and “closed” conformations is different when comparing WT and Val125 OR2T7 simulations. These biophysical and dynamic structural characteristics has been observed in other GPCRs (81,93), including adenosine A2a (39), and are further confirmed through our structural analysis (Fig. 4 f). The angles and distances between TM6 and TM7 exhibit three sampling conformations for both systems: “open,” intermediate, and “closed” (Fig. 5 b). The Val125 simulated structures predominantly sample the “closed” conformation and demonstrate an “open” conformation more similar to the WT intermediate. This switch between these conformational ensembles in OR2T7 appears to be facilitated by the change in interactions between ICL-2, which contains the 125 position, and ICL-3. Other GPCRs have shown that a decreased ability to induce TM6 lateral movement toward an activated or “open” conformation can slow G-protein activity (84,94). Our observations indicate that WT OR2T7 has more helical plasticity and dynamic sampling states, suggesting structural arrangements that facilitate G-protein activity. Conversely, Val125 mutant OR2T7 structures that we sampled demonstrate more helical stability and rigidity, which may influence Gα binding, providing a structural rationale and a possible mechanism for the downregulation of the GPCR-p38 MAPK pathway and its role in GBM.

Conclusions

Collectively, this work suggests that the OR2T7 Val125 mutation impacts the Gα-binding domain, which can lead to decreased expression of RhoB and Casp14, rescuing GBM cells from tumor-suppressor pathways. Experimental work has demonstrated that OR2T7 D125V affects expression of c-Fos, c-Jun, JunB, RhoB, and Casp14 genes, which could be explained via the GPCR-p38 MAPK pathway. Downregulation of RhoB and Casp14 genes has shown that both have important roles in cancer cell survival by evading proapoptotic pathways (70,71,95). Computational studies exploring the structural dynamics of WT and Val125 mutant OR2T7 revealed differences in helical plasticity and structural morphologies, allowing the WT OR2T7 structure to sample more freely between “open” and “closed” conformations while the Val125 mutant OR2T7 structure samples more “closed” state conformations. The differences in helical orientation and position of TM6 are suggested to impact and downregulate G-protein activity, as seen in other GPCRs (94). This work provides initial insight into the key to functional differences between the WT and Val125 OR2T7 structures. The observed biophysical changes as influenced by Val125 have the potential to impact Gα binding and elicit the differences in RhoB and Casp14 expression, thus downregulating apoptotic pathways and rescuing GBM cell lines. With additional experimental validation, the Val125 mutation in OR27T may represent an important prognostic marker and a potential target for glioblastoma for therapeutic development.

Author contributions

R.A., D.N., G.L., and M.B.S. analyzed the function of differentially expressed genes to identify a possible mechanism. R.A. performed bioinformatics analysis of data from TCGA to identify the mutation of interest and identify differentially expressed genes. A.K.S. and A.M.B. performed simulations. A.K.S., D.R.B., and A.M.B. analyzed simulation data. R.A., D.N., G.L., and M.B.S. conducted wet lab experiments and analyzed the results. A.M.B., A.K.S., and R.A. wrote the manuscript. All authors reviewed and approved the manuscript.

Acknowledgments

The authors thank Advanced Research Computing at Virginia Tech for high-performance computing resources. This work was supported by the Edward Via College of Osteopathic Medicine (VCOM) REAP Grant # RA10333.

Declaration of interests

The authors declare no competing interests.

Notes

Editor: Alemayehu A. Gorfe.

Footnotes

Supporting material can be found online at https://doi.org/10.1016/j.bpj.2022.05.009.

Supporting material

Document S1. Figures S1–S19 and Tables S1–S3:

Document S2. Article plus supporting material:

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