Jessica Lilian Bell

Background: Adult-type diffuse gliomas encompass nearly a quarter of all primary tumors found in the CNS, including astrocytoma, oligodendroglioma, and glioblastoma. Histopathological tumor grade and molecular profile distinctly impact patient survival. Despite treatment advancements, patients with recurrent glioma have a very poor clinical outcome, warranting improved risk stratification to determine therapeutic interventions. Various studies have shown that copper is a notable trace element that is crucial for biological processes and has been shown to display pro-tumorigenic functions in cancer, particularly gliomas. Methods: Differential gene expression, Cox regression, and least absolute shrinkage and selection operator regression were used to identify 19 copper-homeostasis-related gene signatures using TCGA lower-grade glioma and glioblastoma (GBM) cohorts. The GLASS Consortium dataset was used as an independent validation cohort. Enrichment analysis revealed the involvement of the signature in various cancer-related pathways and biological processes. Using this CHRG signature, a risk score model and a nomogram were developed to predict survival in glioma patients. Results: Our prognostic CHRG signature stratified patients into high- and low-risk groups, demonstrating robust predictive performance. High-risk groups showed poorer survival outcomes. The nomogram model integrating CHRG signature and clinical features accurately predicted 1-, 3-, and 5-year survival rates in both training and test sets. Conclusions: The identified 19-gene CHRG signature holds promise as a prognostic tool, enabling accurate risk stratification and survival prediction in glioma patients. Integrating this signature with clinical characteristics enhances prognostic accuracy, underscoring its potential clinical utility in optimizing therapeutic strategies and patient care in glioma management.

Supplementary Figure S4. Characterization of the PA2G4-MYCN protein-protein interface. A, BE(2)-C cells were transiently transfected with EV, wildtype PA2G4 or 6 different PA2G4 point mutants for 48 hours, then treated with 100 µg/µl Cycloheximide (CHX) for up to 60 minutes, followed by immunoblot analysis for MYCN protein half-life. B, Differential Scanning Fluorimetry (DSF) showed both the seven amino acid (DHKALST, aa248-254) and large peptide (GGDHKALSTGEDTL, aa246-259) MYCN oligopeptides, along with the MYCN oligopeptide shown not to bind via SPR (DHAALAT) changed the melting temperature of the PA2G4 protein, relative to baseline (i.e. 0mM), in a dose-response manner. Shown are the means of 3 independent experiments {plus minus} SEM. C, An example of the raw data for DHKALST, with the shift to the left correlating to an increase in concentration. D, Raw SPR data for PA2G4 triple mutant (R271A, R272A and S47A) and single mutants (S47A and R272A). Also, raw SPR data for MYCN oligopeptide mutants (DHAALST, DHAALAT and DHKALAT). For the mutants and triple mutations, no binding was observed, thus analysis could not be conducted and is not shown. E, Root Mead Squared Deviation (RMSD) of the peptide over the time of the simulation. After the first 100 frames the peptide is relatively stable. Analysis was only conducted after this time.

Supplementary Figure S6 G-K G, Overall patient survival using Kaplan-Meier survival probability plots from the Cologne data set (http://r2.amc.nl) for PA2G4 mRNA expression subdivided around the median PA2G4 expression level among 477 neuroblastoma patients. H, Kaplan-Meier plot for event-free survival of 649 neuroblastoma patients from the kocak dataset (R2 microarray analysis and visualization platform, http://r2.amc.nl) I, Real-time PCR mRNA expression of PA2G4 among 40 neuroblastoma patient tumors treated at Sydney Children's Hospital, subdivided by MYCN amplification status. J, Multivariate event-free survival analysis using cox regression modelling. The p-values were obtained from the cox-regression analysis. K, Incidence of PA2G4 amplification among a range of different human cancer types within The Cancer Genome Atlas (TCGA). Results were generated using cBioportal for Cancer Genomics (https://cancergenome.nih.gov/). NEPC, neuroendocrine prostate cancer; CS, carcinosarcoma.

Supplementary Figure S5 F-H F), at 72 hours post-transfection of EV or a PA2G4 expression vector. G, Cell viability measured by the Alamar Blue assay and immunoblot analyses using an antibody identifying MYC-tagged PA2G4-p42 protein expression in Kelly and SH-SY5Y cells transfected with EV or the MYC-tagged PA2G4-p42 expression vector at 48 and 72 hours post-transfection. Vinculin was used as loading control. H, Colony formation in vitro by Kelly and SH-SY5Y cells following transfection with either EV or MYC-tagged PA2G4-p42.

Supplementary Figure S1. F, Confocal microscopy of SHEP Tet21N cells using anti-PA2G4 (red) and anti-MYCN (green) antibodies. G, Immunoblot analysis of cytoplasmic and nuclear fractions from BE(2)-C and Kelly human neuroblastoma cell lines with antibodies recognizing PA2G4 and MYCN, or GAPDH and topoisomerase as loading controls. H, Confocal microscopy of neuroblastoma (BE(2)-C and Kelly) cells using anti-PA2G4 (red) and anti-MYCN (green) antibodies. Alexafluor 555 anti-rabbit (to detect PA2G4) and Alexafluor 488 anti-mouse (to detect MYCN) were used as the secondary antibodies. I, Real-time PCR mRNA expression of MYCN and PA2G4 in ganglia from homozygote TH-MYCN+/+ mice, compared to wild type littermate control mice, obtained at different postnatal age (weeks).

Supplementary Figure S6. PA2G4 increases neuroblastoma tumorigenicity. A, Representative images of athymic nude mice inoculated with neuroblastoma (SH-EP) cells stably transfected with either EV control or a PA2G4 expression vector at 10 weeks post-injection. B, Images of tumor formation after mice were culled 12 weeks post-injection. C, Real-time PCR analysis of PA2G4 mRNA expression level in tumors from mice injected with either SH-EP cells overexpressing PA2G4, or SH-EP EV control cells. β2-microglobulin was used as a reference gene for total RNA loading. D, Protein was extracted from SH-EP tumor xenografts overexpressing PA2G4 and control vectors, then analysed for PA2G4-Flag and MYCN expression by immunoblotting using anti-MYCN and anti-PA2G4 antibodies, using a Vinculin loading control. E, Immunoblots of three tumor samples from each siRNA-treated cohort showing the levels of PA2G4 and MYCN protein expression, using a Vinculin loading control. F, Real-time PCR analysis of PA2G4 and MYCN mRNA expression in tumor samples taken from tumour-bearing mice xenografted with BE(2)-C neuroblastoma cells, which had been treated with either nano-particle encapsulated siRNA control, PA2G4 siRNA or PA2G4-p48 siRNA. Data are shown as means and SD derived from 6 mice per group, P-values were calculated by t-test.

Supplementary Figure S2. PA2G4 increases MYCN protein stability. A and B, Representative immunoblots from cycloheximide (CHX) chase assays measuring the half-life of MYCN protein after PA2G4 knockdown (A) or overexpression (B) in BE(2)-C and Kelly cells for 48 hours. Cells were then treated with 100 µg/µl CHX for up to 60 minutes followed by immunoblotting. C, Co-IP of total protein from BE(2)-C cells using IgG, anti-MYCN, anti-PA2G4 antibodies, followed by immunoblotting with anti-MYCN, anti-PA2G4, anti-AURKA, anti-Fbxw7 or anti-vinculin antibodies.

Supplementary Figure S5 F-H F), at 72 hours post-transfection of EV or a PA2G4 expression vector. G, Cell viability measured by the Alamar Blue assay and immunoblot analyses using an antibody identifying MYC-tagged PA2G4-p42 protein expression in Kelly and SH-SY5Y cells transfected with EV or the MYC-tagged PA2G4-p42 expression vector at 48 and 72 hours post-transfection. Vinculin was used as loading control. H, Colony formation in vitro by Kelly and SH-SY5Y cells following transfection with either EV or MYC-tagged PA2G4-p42.