| Literature DB >> 35414102 |
Nadia Trivieri1, Alberto Visioli2, Gandino Mencarelli1, Maria Grazia Cariglia1, Laura Marongiu3, Riccardo Pracella1, Fabrizio Giani2, Amata Amy Soriano1, Chiara Barile1, Laura Cajola2, Massimiliano Copetti4, Orazio Palumbo5, Federico Legnani6, Francesco DiMeco6,7, Leonardo Gorgoglione8, Angelo L Vescovi9,10, Elena Binda11.
Abstract
BACKGROUND: Glioblastoma multiforme (GBM) is an incurable tumor, with a median survival rate of only 14-15 months. Along with heterogeneity and unregulated growth, a central matter in dealing with GBMs is cell invasiveness. Thus, improving prognosis requires finding new agents to inhibit key multiple pathways, even simultaneously. A subset of GBM stem-like cells (GSCs) may account for tumorigenicity, representing, through their pathways, the proper cellular target in the therapeutics of glioblastomas. GSCs cells are routinely enriched and expanded due to continuous exposure to specific growth factors, which might alter some of their intrinsic characteristic and hide therapeutically relevant traits.Entities:
Keywords: Anti-GSCs patient-tailored strategies; GBM cancer stem cells (GSCs); GSCs biology and biomarkers; Glioblastoma; Mitogen-independence
Mesh:
Substances:
Year: 2022 PMID: 35414102 PMCID: PMC9004109 DOI: 10.1186/s13046-022-02333-1
Source DB: PubMed Journal: J Exp Clin Cancer Res ISSN: 0392-9078
Characteristics of patients and samples involved in the study
| Patient #1 | M | 79 | WT | NO | C228T | GBM |
| Patient #2 | M | 76 | WT | NO | C228T | GBM |
| Patient #8 | M | 76 | WT | YES | C228T | GBM |
| Patient #9 | M | 79 | WT | YES | C228T | GBM |
| Patient #14 | F | 80 | WT | NO | C228T | GBM |
| Patient #11 | M | 71 | WT | NO | C228T | GBM |
| Patient #6 | F | 52 | WT | NO | C250T | GBM |
| Patient #12 | M | 43 | WT | NO | C228T | GBM |
| Patient #7 | F | 44 | WT | NO | C228T | GBM -GLIOSARCOMA |
| Patient #13 | M | 42 | WT | NO | C228T | GBM |
| Patient #16 | M | 70 | WT | NO | C228T | GBM |
| Patient #17 | F | 72 | WT | NO | C250T | GBM |
| Patient #3 | M | 62 | WT | NO | C228T | GBM |
| Patient #5 | F | 56 | WT | NO | C228T | GBM |
| Patient #10 | F | 73 | WT | YES | C228T | GBM |
| Patient #15 | M | 62 | WT | NO | C228T | GBM |
Key resources table
| REAGENT or RESOURCE | SOURCE | IDENTIFIER |
|---|---|---|
| Mouse monoclonal anti-Human Nuclei | Merck - Millipore | Cat# MAB1281; RRID: AB_94090 |
| Rabbit polyclonal anti Laminin | Merck – Millipore (Sigma Aldrich) | Cat# L9393; RRID: AB_477163 |
| Goat polyclonal anti EphA2 | R&D System | Cat# AF3035; RRID: AB_2277943 |
| Anti-Ki-67 antibody | Millipore | Cat# AB9260; RRID: AB_2142366 |
| Rabbit polyclonal anti Wnt5a | LS Biosciences | Cat# LS-C160634; RRID: AB_2736865 |
| Mouse monoclonal anti BMPR 1b | R&D System | Cat# MAB5051; RRID: AB_2064101 |
| Rabbit polyclonal Glial Fibrillary Acidic Protein (GFAP) | Agilent | Cat# Z0334; RRID: AB_10013382 |
| Mouse Anti-Galactocerebroside C (GalC) | Millipore | Cat# MAB342; RRID: AB_94857 |
| Purified anti-Tubulin beta 3 (TUBB3) | Biolegend | Cat# 801201; RRID: AB_2313773 |
| Goat anti mouse AlexaFluor488 | Thermo Fisher | Cat#; RRID:AB_2534069 |
| Goat anti mouse AlexaFluor546 | Thermo Fisher | Cat# A11003; RRID:AB_141370 |
| Goat anti rabbit AlexaFluor488 | Thermo Fisher | Cat# A11008; RRID:AB_143165 |
| Donkey anti goat AlexaFluor488 | Thermo Fisher | Cat# A11055; RRID:AB_2534102 |
| Goat anti rabbit AlexaFluor546 | Thermo Fisher | Cat# A11010; RRID:AB_2534077 |
| Scid-Beige Mouse: CB17.Cg-PrkdcscidLystbg-J/Crl | Charles River | Cat# CRL:250; RRID:IMSR_ CRL:250 |
| AxioVision Imaging System | Zeiss | RRID:SCR_002677 |
| NIS-Elements | Nikon | RRID:SCR_014329 |
| GraphPad Prism | RRID:SCR_002798 | |
| Integrative genomic viewer (IGV) | RRID:SCR_011793 | |
| R Project for Statistical Computing | RRID:SCR_001905 | |
| PARTEK GENOMICS SUITE | RRID:SCR_011860 | |
| ARRAYEXPRESS REPOSITORY | RRID:SCR_000120 | |
| VARSCAN | RRID:SCR_006849 | |
| ANNOVAR | RRID:SCR_012821 | |
| GATK | RRID:SCR_001876 | |
| MutationTaster | RRID:SCR_010777 | |
| PolyPhen: Polymorphism Phenotyping | RRID:SCR_013189 | |
| PROVEAN | RRID:SCR_002182 | |
| SIFT | RRID:SCR_012813 | |
| Circos | RRID:SCR_011798 | |
| Ingenuity Pathway Analysis | RRID:SCR_008653 | |
| GISTIC | RRID:SCR_000151 | |
| SAMTOOLS | RRID:SCR_002105 | |
| CustomCDF | RRID:SCR_018527 | |
| Entrez Gene | RRID:SCR_002473 | |
| BaseSpace | RRID:SCR_011881 | |
| CHROMAS | RRID:SCR_000598 | |
| QIAXCEL | QIAGEN | RRID:SCR_018624 |
Fig. 1I-GSCs can be isolated from GBM surgery specimens in the absence of mitogenic stimulation. A. GFs-independent (I-GSCs) (top) and dependent GSCs (D-GSCs) (bottom) can be either isolated from the very same patient’s tissue across subtypes, with the former exhibiting many adhesion-related protrusions (arrowheads) and the latter typical rounded morphology. B-C. Significant differences in the expansion rate (B) and self-renewal potential (C) between I- and D-GSCs across subtypes, with the former comprising slower-dividing GSCs with a lower clonogenicity. *P < 0.05 I-GSCs vs. D-GSCs, hierarchical linear model for repeated measurements and ***P < 0.001, **P < 0.01, *P < 0.05 and P < 0.0001 I-GSCs vs. D-GSCs, one-way Student’s t-test in B and C, respectively. Lines I-GSCs and D-GSCs #1 (TCGA-CL GSCs, red), #6 (TCGA-MS, blue) and #15 (TCGA-PN, green) are shown as representative examples in B. Data are mean ± SD (B) and mean ± SEM (C) (n = 3). D. When exposed to mitogens, I-GSCs’ proliferation closely mirrors that one of D-GSCs, regardless of subtype (TCGA-CL GSCs, right; TCGA-MS GSCs, middle; TCGA-PN GSCs, right). ***P < 0.001 I-GSCs vs. D-GSCs, hierarchical linear model for repeated measurements. Data are mean ± SD (n = 3). E. Violin plot displaying the different enrichment of genes associated to stemness, differentiation and invasion in I-GSCs vs. D-GSCs across subtypes, as detected by qPCR. P-values are from Kruskal-Wallis test. F. Dot plots showing flow cytometric analysis confirming the enrichment of Wnt5a in I-GSCs across subtypes when compared to D-GSCs, shown to upregulate EphA2. Lines I-GSCs and D-GSCs #1 (TCGA-CL GSCs), #5 (TCGA-PN GSCs) and #11 (TCGA-MS GSCs) are shown as representative examples (n = 3). G. High level of WNT5A combined with low EPHA2 expression is associated with lower GBM patients’ survival according to TCGA public dataset (P = 0.0063 and P = 0.0259; n = 91, Log-rank and Gehan-Breslow-Wilcoxon test), as depicted by Kaplan-Meier plots. H-I. In vitro migration assay showing that, irrespective of the molecular subtype, I-GSCs migrate and invade more efficiently than their D-GSCs counterpart (H). I Blockade of Wnt5a signaling by Wnt5a-endogenous antagonists (rhWnt3a; middle and rhSFRP1; right) lessens I-GSCs’ exacerbated invasiveness (top), whereas enhancement of Wnt5a expression in D-GSCs by stable lentiviral-mediated overexpression (LV-Wnt5a; middle) or by exposure to rhWnt5a (right) elicits cell migration (bottom). Bars in A, H-I, 100um, 50um. Quantification in H-I is shown as mean ± SEM. ***P < 0.001, **P < 0.01, ns not significant, one-way Student’s t-test and ANOVA Tukey’s multiple comparison test
Fig. 2I-GSCs are endowed in vivo with enhanced tumorigenic ability. A. GBM xenografts derived from I-GSCs display higher growth than those generated by D-GSCs sibling regardless of the transcriptional subtype, as depicted by quantitative time-course bioluminescence analysis. Data are mean ± SEM. P-values are from hierarchical linear model; n = 5 mice/group. B. Mice carrying luc-I- and D-GSCs cells are imaged from 7 days post-transplantation (DPT) to the endpoint. C. Serial immunohistochemical reconstructions confirming that I-GSCs give rise to more extended and invasive tumors than those from D-GSCs injection. Bar, 1 mm. D. Kaplan-Meier plot of survival demonstrating that animals receiving I-GSCs die much earlier than those implanted with their sibling D-GSCs. P-values are from Log-rank and Gehan-Breslow-Wilcoxon test
Fig. 3I-GSCs’ transcriptional profile is defined by migration and invasiveness. A-B Unsupervised hierarchical clustering analysis based on global gene expression profile of nine I-GSCs lines (blue), D-GSCs (red) counterpart and their GBM tissues (TEX; green) reporting a matching transcriptional signature between I-GSCs and tissue samples. Samples are coded by color. A dual-color code represents genes over- (red) and under-represented (blue), respectively (A). B Venn diagram confirming the exclusive over-expression in I-GSCs of genes mainly involved in cell migration (FDR < 0.05 and FC = 2). C. Hierarchical clustering using 66 differentially expressed genes when comparing I-GSCs to D-GSCs (left). Higher overlap of genes between I-GSCs and their original GBM tissue as compared to D-GSCs versus the same tissue, as reported by Venn diagram (right). D. Volcano plots based on expression data showing the higher infiltrative and mature, “astrocyte-like” profile of I-GSCs vs D-GSCs. Significant hits are depicted in red and blue. The top candidates are labelled. E. When compared to their D-GSCs siblings, I-GSCs’ overexpress transcripts belonging to biological functions as cell death, invasion and inflammatory/immune response, whereas downregulated mRNAs are mainly involved in cell cycle, cell proliferation and survival processes. Red and blue bars count for up- and downregulated genes, respectively. F. Distribution of the frequently mutated genes in GBM across subtype in both GSCs population and their tissue. **P < 0.01, *P < 0.05, Fisher’s exact test
Fig. 4Ex vivo effects of PepA and ephrinA1-Fc treatments on GSCs. A Ex vivo treatment of GSCs with exogenous PepA hinders invasiveness of either I- (top) or D-GSCs (bottom) regardless of subtype. Bars, 50um Quantification is shown in B as mean ± SEM. ***P < 0.001, *P < 0.05, ns, not significant, one-way Student’s t-test; n = 3. C. Exposure of I- (left) and D-GSCs (right) to PepA (green line), ephrinA1-Fc (red line) or a combination of both (purple line) lessens steady growth of both GSCs to nearly half than in control GSCs, showing a clear additive effect of the two molecules. Data are mean ± SD. ***P < 0.001 I-GSCs vs. D-GSCs, hierarchical linear model for repeated measurements; n = 3
Fig. 5A combinatorial PepA/ephrinA1-Fc-manipulation approach impairs tumorigenicity and invasiveness of GSCs cells. A. Quantitative analysis of luc-GSCs signal showing that both PepA and ephrinA1-Fc hinder I-GSCs-derived tumors’ growth (left) and, to a lesser extent, of their D-GSCs counterpart (right) and that the combined use of the two molecules has an additive effect. Data are mean ± SEM. ***P < 0.001, *P < 0.05, Dunnett’s multiple comparison test; n = 5 mice. B. Imaging of luciferase-tagged I- and D-GSCs injected into the brain of Scid/bg mice showing that after 23 and 34 days, respectively, untreated mice develop larger and spreaded tumors than PepA and ephrinA1-Fc-infused mice. Tumor growth is markedly inhibited with the combination of both molecules. C. Brain sections confirming that tumors from mice carrying I-GSCs or D-GSCs cells and infused with vehicle proliferated and spread through the brain parenchyma more than those infused either with PepA or ephrinA1-Fc, being the combination of both even more efficacious in reducing cell proliferation and invasiveness. Bar, 1 mm. D. Survival of mice harboring I-GSCs (left) and D-GSCs-tumors (right) is significantly enhanced when infused with PepA (blue bar) and ephrinA1-Fc (red bar) alone, or even more with the combination of the two molecules (green bar). A league table of comparison by Log-rank is shown; n = 5 mice