Combining single-cell sequencing and spatial transcriptome sequencing to identify exosome-related features of glioblastoma and constructing a prognostic model to identify BARD1 as a potential therapeutic target for GBM patients
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ABSTRACT:
SUBMITTER: Zhao S
PROVIDER: S-EPMC10505933 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:Neural stem cells (NSCs) offer great potential for regenerative medicine due to their excellent ability to differentiate into various specialized cell types of the brain. In the central nervous system (CNS), NSC renewal and differentiation are under strict control by the regulation of the pivotal SLIT-ROBO Rho GTPase activating protein 2 (SRGAP2)-Family with sequence similarity 72 (FAM72) master gene (i.e., |-SRGAP2-FAM72-|) via a divergent gene transcription activation mechanism. If the gene transcription control unit (i.e., the intergenic region of the two sub-gene units, SRGAP2 and FAM72) gets out of control, NSCs may transform into cancer stem cells and generate brain tumor cells responsible for brain cancer such as glioblastoma multiforme (GBM). Here, we discuss the surveillance of this |-SRGAP2-FAM72-| master gene and its role in GBM, and also in light of FAM72 for diagnosing various types of cancers outside of the CNS.
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Project description:Characterization of gene expression for a panel of 50 in vitro and in vivo models of glioblastoma (GBM). Models include subcutaneously established xenograft lines, orthotopically grown subcutaneously established xenograft lines, serum derived cell lines and stem cell media derived cell lines. Multiple replicates of each line were run on different dates to determine the effect of batch and processing date on reproducibility of gene expression profiles 117 samples analyzed from 50 distinct GBM xenografts or cell lines. Biological replicates from the same passage number were included for many, but not all, of the lines.
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Project description:: Glioblastoma multiforme (GBM) is the most malignant form of primary brain tumour with extremely poor prognosis. The current standard of care for newly diagnosed GBM includes maximal surgical resection followed by radiotherapy and adjuvant chemotherapy. The introduction of this protocol has improved overall survival, however recurrence is essentially inevitable. The key reason for that is that the surgical treatment fails to eradicate GBM cells completely, and adjacent parenchyma remains infiltrated by scattered GBM cells which become the source of recurrence. This stimulates interest to any supplementary methods which could help to destroy residual GBM cells and fight the infiltration. Photodynamic therapy (PDT) relies on photo-toxic effects induced by specific molecules (photosensitisers) upon absorption of photons from a light source. Such toxic effects are not specific to a particular molecular fingerprint of GBM, but rather depend on selective accumulation of the photosensitiser inside tumour cells or, perhaps their greater sensitivity to the effects, triggered by light. This gives hope that it might be possible to preferentially damage infiltrating GBM cells within the areas which cannot be surgically removed and further improve the chances of survival if an efficient photosensitiser and hardware for light delivery into the brain tissue are developed. So far, clinical trials with PDT were performed with one specific type of photosensitiser, protoporphyrin IX, which tends to accumulate in the cytoplasm of the GBM cells. In this review we discuss the idea that other types of molecules which build up in mitochondria could be explored as photosensitisers and used for PDT of these aggressive brain tumours.
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Project description:PurposeGlioblastoma (GBM) is one of the most aggressive brain tumors with high mortality, and tumor-derived exosomes provide new insight into the mechanisms of GBM tumorigenesis, metastasis and therapeutic resistance. We aimed to establish an exosome-derived competitive endogenous RNA (ceRNA) network for constructing a prognostic model for GBM.MethodsWe obtained the expression profiles of long noncoding RNAs (lncRNAs), miRNAs, and mRNAs from the GEO and TCGA databases and identified differentially expressed RNAs in GBM to construct a ceRNA network. By performing lasso and multivariate Cox regression analyses, we identified optimal prognosis-related differentially expressed lncRNAs (DElncRNAs) and generated a risk score model termed the exosomal lncRNA (exo-lncRNA) signature. The exo-lncRNA signature was subsequently validated in the CGGA GBM cohort. Finally, a novel prognostic nomogram was constructed based on the exo-lncRNA signature and clinicopathological parameters and validated in the CGGA external cohort. Based on the ceRNA hypothesis, oncocers were identified based on highly positive correlations between lncRNAs and mRNAs mediated by the same miRNAs. Furthermore, regression analyses were performed to assess correlations between the expression abundances of lncRNAs in tumors and exosomes.ResultsA total of 45 DElncRNAs, six DEmiRNAs, and 38 DEmRNAs were identified, and an exosome-derived ceRNA network was built. Three optimal prognostic-related DElncRNAs, HOTAIR (HR=0.341, P<0.001), SOX21-AS1 (HR=0.30, P<0.001), and STEAP3-AS1 (HR=2.47, P<0.001), were included to construct the exo-lncRNA signature, which was further proven to be an independent prognostic factor. The novel prognostic nomogram was constructed based on the exo-lncRNA signature, patient age, pharmacotherapy, radiotherapy, IDH mutation status, and MGMT promoter status, with a concordance index of 0.878. ROC and calibration plots both suggested that the nomogram had beneficial discrimination and predictive abilities. A total of 11 pairs of prognostic oncocers were identified. Regression analysis suggested excellent consistency of the expression abundance of the three exosomal lncRNAs between exosomes and tumor tissues.ConclusionsExosomal lncRNAs may serve as promising prognostic predictors and therapeutic targets. The prognostic nomogram based on the exo-lncRNA signature might provide an intuitive method for individualized survival prediction and facilitate better treatment strategies.
| S-EPMC7973265 | biostudies-literature
Project description:Glioblastoma (GBM) is the most common and highly lethal primary malignant brain tumor in adults. There is a dire need for easily accessible, noninvasive biomarkers that can delineate underlying molecular activities and predict response to therapy. To this end, we sought to identify subtypes of GBM, differentiated solely by quantitative magnetic resonance (MR) imaging features, that could be used for better management of GBM patients. Quantitative image features capturing the shape, texture, and edge sharpness of each lesion were extracted from MR images of 121 single-institution patients with de novo, solitary, unilateral GBM. Three distinct phenotypic "clusters" emerged in the development cohort using consensus clustering with 10,000 iterations on these image features. These three clusters--pre-multifocal, spherical, and rim-enhancing, names reflecting their image features--were validated in an independent cohort consisting of 144 multi-institution patients with similar tumor characteristics from The Cancer Genome Atlas (TCGA). Each cluster mapped to a unique set of molecular signaling pathways using pathway activity estimates derived from the analysis of TCGA tumor copy number and gene expression data with the PARADIGM (Pathway Recognition Algorithm Using Data Integration on Genomic Models) algorithm. Distinct pathways, such as c-Kit and FOXA, were enriched in each cluster, indicating differential molecular activities as determined by the image features. Each cluster also demonstrated differential probabilities of survival, indicating prognostic importance. Our imaging method offers a noninvasive approach to stratify GBM patients and also provides unique sets of molecular signatures to inform targeted therapy and personalized treatment of GBM.
| S-EPMC4666025 | biostudies-literature
Project description:BackgroundGlioblastoma (GBM) is a primary brain tumor with a 5-year survival rate of ≤5%. We have shown earlier that GBM-antibody-linked curcumin (CC) and also phytosomal curcumin (CCP) rescue 50-60% of GBM-bearing mice while repolarizing the tumor-associated microglia/macrophages (TAM) from the tumor-promoting M2-type to the tumoricidal M1-type. However, systemic application of CCP yields only sub-IC50 concentrations of CC in the plasma, which is unlikely to kill GBM cells directly. This study investigates the role of CC-evoked intra-GBM recruitment of activated natural killer (NK) cells in the elimination of GBM and GBM stem cells.MethodsWe have used an immune-competent syngeneic C57BL6 mouse model with the mouse-GBM GL261 cells orthotopically implanted in the brain. Using immunohistochemistry and flow cytometry, we have quantitatively analyzed the role of the intra-GBM-recruited NK cells by (i) injecting (i.p.) the NK1.1 antibody (NK1.1Ab) to temporarily eliminate the NK cells and (ii) blocking NK recruitment by injecting an IL12 antibody (IL12Ab). The treatment cohorts used randomly-chosen GL261-implanted mice and data sets were compared using two-tailed t-test or ANOVA.ResultsCCP treatment caused the GBM tumor to acquire M1-type macrophages (50-60% of the TAM) and activated NK cells. The treatment also elicited (a) suppression of the M2-linked tumor-promoting proteins STAT3, ARG1, and IL10, (b) induction of the M1-linked anti-tumor proteins STAT1 and inducible nitric oxide synthase in the TAM, (c) elimination of CD133(+) GBM stem cells, and (d) activation of caspase3 in the GBM cells. Eliminating intra-GBM NK cell recruitment caused a partial reversal of each of these effects. Concomitantly, we observed a CCP-evoked dramatic induction of the chemokine monocyte chemotactic protein-1 (MCP-1) in the TAM.ConclusionsThe recruited NK cells mediate a major part of the CCP-evoked elimination of GBM and GBM stem cells and stabilization of the TAM in the M1-like state. MCP-1 is known to activate peripheral M1-type macrophages to secrete IL12, an activator of NK cells. Based on such observations, we postulate that by binding to peripheral M1-type macrophages and IL12-activated NK cells, the brain-released chemokine MCP-1 causes recruitment of peripheral immune cells into the GBM, thereby causing destruction of the GBM cells and GBM stem cells.
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Project description:ObjectiveHuman tumor cell lines form the basis of the majority of present day laboratory cancer research. These models are vital to studying the molecular biology of tumors and preclinical testing of new therapies. When compared to traditional adherent cell lines, suspension cell lines recapitulate the genetic profiles and histologic features of glioblastoma multiforme (GBM) with higher fidelity. Using a modified neural stem cell culture technique, here we report the characterization of GBM cell lines including GBM variants.MethodsTumor tissue samples were obtained intra-operatively and cultured in neural stem cell conditions containing growth factors. Tumor lines were characterized in vitro using differentiation assays followed by immunostaining for lineage-specific markers. In vivo tumor formation was assayed by orthotopic injection in nude mice. Genetic uniqueness was confirmed via short tandem repeat (STR) DNA profiling.ResultsThirteen oncosphere lines derived from GBM and GBM variants, including a GBM with PNET features and a GBM with oligodendroglioma component, were established. All unique lines showed distinct genetic profiles by STR profiling. The lines assayed demonstrated a range of in vitro growth rates. Multipotency was confirmed using in vitro differentiation. Tumor formation demonstrated histologic features consistent with high grade gliomas, including invasion, necrosis, abnormal vascularization, and high mitotic rate. Xenografts derived from the GBM variants maintained histopathological features of the primary tumors.ConclusionsWe have generated and characterized GBM suspension lines derived from patients with GBMs and GBM variants. These oncosphere cell lines will expand the resources available for preclinical study.
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Project description:BackgroundThis study aimed to use single-cell RNA-seq (scRNA-seq) to discover marker genes in endothelial cells (ECs) and construct a prognostic model for glioblastoma multiforme (GBM) patients in combination with traditional high-throughput RNA sequencing (bulk RNA-seq).MethodsBulk RNA-seq data was downloaded from The Cancer Genome Atlas (TCGA) and The China Glioma Genome Atlas (CGGA) databases. 10x scRNA-seq data for GBM were obtained from the Gene Expression Omnibus (GEO) database. The uniform manifold approximation and projection (UMAP) were used for downscaling and cluster identification. Key modules and differentially expressed genes (DEGs) were identified by weighted gene correlation network analysis (WGCNA). A non-negative matrix decomposition (NMF) algorithm was used to identify the different subtypes based on DEGs, and multivariate cox regression analysis to model the prognosis. Finally, differences in mutational landscape, immune cell abundance, immune checkpoint inhibitors (ICIs)-associated genes, immunotherapy effects, and enriched pathways were investigated between different risk groups.ResultsThe analysis of scRNA-seq data from eight samples revealed 13 clusters and four cell types. After applying Fisher's exact test, ECs were identified as the most important cell type. The NMF algorithm identified two clusters with different prognostic and immunological features based on DEGs. We finally built a prognostic model based on the expression levels of four key genes. Higher risk scores were significantly associated with poorer survival outcomes, low mutation rates in IDH genes, and upregulation of immune checkpoints such as PD-L1 and CD276.ConclusionWe built and validated a 4-gene signature for GBM using 10 scRNA-seq and bulk RNA-seq data in this work.
| S-EPMC9724299 | biostudies-literature
Project description:BackgroundGlioblastoma (GBM) is a highly malignant brain tumor with poor survival and prognosis. Randomized trials have demonstrated that chemotherapy improves survival in patients with GBM. This study aims to examine the clinical characteristics that are potentially associated with the efficacy of chemotherapy and the risk factors of GBM.MethodsA total of 25,698 patients diagnosed with GBM were identified between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER). The clinical and demographic variables between groups were examined by Student's t-test and Pearson's chi-square test. GBM-specific survival (GBMSS) and overall survival (OS) were evaluated using the Kaplan-Meier method with the log-rank test. Univariable and multivariable analyses were also performed using the Cox proportional hazards model to identify statistically significant prognostic factors.ResultsPatients who received chemotherapy had better overall survival (median OS 13 vs. Three months, HR = 1.9224, 95%CI 1.8571-1.9900, p < 0.0001) and better GBMSS (median GBMSS of 12 vs. Three months, HR = 1.9379, 95%CI 1.8632-2.0156, p < 0.0001), compared to patients who did not. Further subgroup analysis revealed that among patients who underwent chemotherapy, those who were younger, with a supratentorial tumor, received surgery, or radiotherapy had both improved OS and GBMSS. Age, race, tumor location, tumor size, and treatments were identified as independent prognostic factors by multivariable analyses for patients with glioblastoma.ConclusionPatients with GBM who were younger (< 65 years), underwent surgery, or radiotherapy can benefit more from chemotherapeutic regimens. Age, race, tumor size, tumor location, surgery, radiotherapy, and chemotherapy were factors associated with the prognosis of patients with GBM.
| S-EPMC7816395 | biostudies-literature
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