Identification of Novel Transcriptome Signature as a Potential Prognostic Biomarker for Anti-Angiogenic Therapy in Glioblastoma Multiforme.
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ABSTRACT:
SUBMITTER: Zheng S
PROVIDER: S-EPMC7957709 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Glioblastoma multiforme (GBM) is the most common and devastating type of primary brain tumor, with a median survival time of only 15 months. Having a clinically applicable genetic biomarker would lead to a paradigm shift in precise diagnosis, personalized therapeutic decisions, and prognostic prediction for GBM. Radiogenomic profiling connecting radiological imaging features with molecular alterations will offer a noninvasive method for genomic studies of GBM. To this end, we analyzed over 3800 glioma and GBM cases across four independent datasets. The Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases were employed for RNA-Seq analysis, whereas the Ivy Glioblastoma Atlas Project (Ivy-GAP) and The Cancer Imaging Archive (TCIA) provided clinicopathological data. The Clinical Proteomic Tumor Analysis Consortium Glioblastoma Multiforme (CPTAC-GBM) was used for proteomic analysis. We identified a simple three-gene transcriptome signature-SOCS3, VEGFA, and TEK-that can connect GBM's overall prognosis with genes' expression and simultaneously correlate radiographical features of perfusion imaging with SOCS3 expression levels. More importantly, the rampant development of neovascularization in GBM offers a promising target for therapeutic intervention. However, treatment with bevacizumab failed to improve overall survival. We identified SOCS3 expression levels as a potential selection marker for patients who may benefit from early initiation of angiogenesis inhibitors.
| S-EPMC7564118 | biostudies-literature
Project description:BackgroundAlthough anti-angiogenic therapy (AATx) holds great promise for treatment of malignant gliomas, its therapeutic efficacy is not well understood and can potentially increase the aggressive recurrence of gliomas. It is essential to establish sensitive, noninvasive biomarkers that can detect failure of AATx and tumor recurrence early so that timely adaptive therapy can be instituted. We investigated the efficacy of MRI biomarkers that can detect response to different classes of AATxs used alone or in combination with radiation.MethodsMurine intracranial glioma xenografts (NOD/SCID) were treated with sunitinib, VEGF-trap or B20 (a bevacizumab equivalent) alone or in combination with radiation. MRI images were acquired longitudinally before and after treatment, and various MRI parameters (apparent diffusion coefficient, T1w + contrast, dynamic contrast-enhanced [DCE], initial area under the contrast enhancement curve, and cerebral blood flow) were correlated to tumor cell proliferation, overall tumor growth, and tumor vascularity.ResultsCombinatorial therapies reduced tumor growth rate more efficiently than monotherapies. Apparent diffusion coefficient was an accurate measure of tumor cell density. Vascular endothelial growth factor (VEGF)-trap or B20, but not sunitinib, resulted in significant reduction or complete loss of contrast enhancement. This reduction was not due to a reduction in tumor growth or microvascular density, but rather was explained by a reduction in vessel permeability and perfusion. We established that contrast enhancement does not accurately reflect tumor volume or vascular density; however, DCE-derived parameters can be used as efficient noninvasive biomarkers of response to AATx.ConclusionsMRI parameters following therapy vary based on class of AATx. Validation of clinically relevant MRI parameters for individual AATx agents is necessary before incorporation into routine practice.
| S-EPMC4022230 | biostudies-literature
Project description:Glioblastoma multiforme (GBM) possesses florid angiogenesis. However, the anti-angiogenic agent, Bevacizumab, did not improve overall survival of GBM patients. For more durable anti-angiogenic treatment, we interrogated resistant mechanisms of GBM against Bevacizumab. Serial orthotopic transplantation of in vivo Bevacizumab-treated GBM cells provoked complete refractoriness to the anti-angiogenic treatment. These tumors were also highly enriched with malignant phenotypes such as invasiveness, epithelial to mesenchymal transition, and stem-like features. Through transcriptome analysis, we identified that Talin1 (TLN1) significantly increased in the refractory GBMs. Inhibition of TLN1 not only attenuated malignant characteristics of GBM cells but also reversed the resistance to the Bevacizumab treatment. These data implicate TLN1 as a novel therapeutic target for GBM to overcome resistance to anti-angiogenic therapies.
| S-EPMC4694986 | biostudies-literature
Project description:BackgroundGlioblastoma multiforme (GBM) is the most malignant type of glioma. GBM tumors grow rapidly, have a high degree of malignancy, and are characterized by a fast disease progression. Unfortunately, there is a lack of effective treatments. An effective strategy for the treatment of GBM would be to identify key biomarkers correlating with the occurrence and progression of GBM and developing these biomarkers into therapeutic targets.Method and resultsIn this study, using integrated bioinformatics analysis, we identified differentially expressed genes (DEGs), including 130 genes that were upregulated in GBM compared to normal brain tissue, and 128 genes that were downregulated in GBM. Based on Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis, these genes were associated with regulation of tumor cell adhesion, differentiation, morphology in GBM and were mainly enriched in Complement and coagulation cascades pathway. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to construct a Protein-Protein Interaction network. Ten hub genes were identified, including FN1, CD44, MYC, CDK1, SERPINE1, COL3A1, COL1A2, LOX, POSTN and EZH2, all of which were significantly upregulated in GBM, these results were confirmed by oncomine database exploration. Alteration analysis of hub genes found that patients with alteration in at least one of the hub genes showed shorter median survival times (p = 0.013) and shorter median disease-free survival times (p = 2.488E-3) than patients without alterations in any of the hub genes. Multiple tests for survival analysis showed that among individual hub genes only expression of LOX was correlated with patient survival (P < 0.05).GDS4467 data set was used to analyze the expression of LOX in gliomas with different degrees of malignancy, and it was found that the expression level of LOX was positively correlated with the malignant degree of gliomas.By analyzing GDS 4535 data set showed that the expression level of LOX was positively correlated with the differentiation degree of GBM cells CONCLUSION: This research suggests that FN1, CD44, MYC, CDK1, SERPINE1, COL3A1, COL1A2, LOX, POSTN and EZH2 are key genes in GBM. However, only LOX is correlated with patient survival and promotes glioblastoma cell differentiation and tumor recurrence. LOX may be a candidate prognostic biomarker and potential therapeutic target for GBM.
| S-EPMC10423882 | biostudies-literature
Project description:Glioblastoma multiforme (GBM) is the deadliest type of brain tumor. The median survival time for patients with GBM is only 15 months, even following maximal surgical resection and chemotherapy and radiation therapy. A genetic biomarker could enable a paradigm shift in precise diagnosis, personalized therapeutics and prognosis. In this study, we employed the Chinese Glioma Genome Atlas, The Cancer Genome Atlas, and the Ivy Glioblastoma Atlas Project databases for RNA sequencing (RNA-seq) analysis and clinicopathological studies. We demonstrated that elevated expression of the RNF7, TCEB1, SOCS1 and SOCS3 genes, which encode components of cullin5-RING E3 ligase (CRL5), predict unfavorable GBM prognoses. In GBM and glioma cases carrying IDH1 mutations, SOCS1 and SOCS3 methylation was increased and their expression was downregulated. This study has thus identified a simple transcriptome signature for GBM prognosis.
| S-EPMC7521521 | biostudies-literature
Project description:Anti-angiogenic therapy has become an important component in the treatment of many solid tumors given the importance of adequate blood supply for tumor growth and metastasis. Despite promising preclinical data and early clinical trials, anti-angiogenic agents have failed to show a survival benefit in randomized controlled trials of patients with glioblastoma. In particular, agents targeting vascular endothelial growth factor (VEGF) appear to prolong progression free survival, possibly improve quality of life, and decrease steroid usage, yet the trials to date have demonstrated no extension of overall survival. In order to improve duration of response and convey a survival benefit, additional research is still needed to explore alternative pro-angiogenic pathways, mechanisms of resistance, combination strategies, and biomarkers to predict therapeutic response.
| S-EPMC5398985 | biostudies-literature
Project description:BackgroundGliomas are the most common intracranial tumors and are classified as I-IV. Among them, glioblastoma multiforme (GBM) is the most common invasive glioma with a poor prognosis. New molecular biomarkers that can predict clinical outcomes in GBM patients must be identified, which will help comprehend their pathogenesis and supply personalized treatment. Our research revealed four powerful survival indicators in GBM by reanalyzing microarray data and genetic sequencing data in public databases. Moreover, it unraveled new potential therapeutic targets which could help improve the survival time and quality of life of GBM patients.Materials and methodsTo identify prognostic signatures in GBMs, we analyzed the gene profiling data of GBM and standard brain samples from the Gene Expression Omnibus, including four datasets and RNA sequencing data from The Cancer Genome Atlas (TCGA) containing 152 glioblastoma tissues. We performed the differential analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, weighted gene co-expression network analysis (WGCNA) and Cox regression analysis.ResultsAfter differential analysis in GSE12657, GSE15824, GSE42656 and GSE50161, overlapping differentially expressed genes were identified. We identified 110 up-regulated DEGs and 75 down-regulated DEGs in the GBM samples. Significantly enriched subclasses of the GO classification of these genes included mitotic sister chromatid separation, mitotic nuclear division and so on. In KEGG pathway analysis, the most abundant terms were ECM-receptor interaction and protein digestion and absorption. WGCNA analysis was performed on these 185 DEGs in 152 glioblastoma samples obtained from TCGA, and gene co-expression networks were constructed. We then performed a multivariate Cox analysis and established a Cox proportional hazards regression model using the top 20 genes significantly correlated with survival time. We identified a four-protein prognostic signature that could divide patients into high-risk and low-risk groups. Increased expression of SLC12A5, CCL2, IGFBP2, and PDPN was associated with increased risk scores. Finally, the K-M curves confirmed that these genes could be used as independent predictors of survival in patients with glioblastoma.ConclusionOur analytical study identified a set of potential biomarkers that could predict survival and may contribute to successful treatment of GBM patients.
| S-EPMC7136556 | biostudies-literature
Project description:The incurability of malignant glioblastomas is mainly attributed to their highly invasive nature coupled with resistance to chemo- and radiation therapy. Because invasiveness is partially dictated by the proteins these tumors secrete we used SILAC to characterize the secretomes of four glioblastoma cell lines (LN18, T98, U118 and U87). Although U87 and U118 cells both secreted high levels of well-known invasion promoting proteins, a Matrigel invasion assay showed U87 cells to be eight times more invasive than U118 cells, suggesting that additional proteins secreted by U87 cells may contribute to the highly invasive phenotype. Indeed, we identified a number of proteins highly or exclusively expressed by U87 cells as compared to the less invasive cell lines. The most striking of these include ADAM9, ADAM10, cathepsin B, cathepsin L1, osteopontin, neuropilin-1, semaphorin-7A, suprabasin, and chitinase-3-like protein 1. U87 cells also expressed significantly low levels of some cell adhesion proteins such as periostin and EMILIN-1. Correlation of secretome profiles with relative levels of invasiveness using Pavlidis template matching further indicated potential roles for these proteins in U87 glioblastoma invasion. Antibody inhibition of CH3L1 reduced U87 cell invasiveness by 30%.
| S-EPMC3136381 | biostudies-literature
Project description:Glioblastoma is the most aggressive brain tumor with a median survival ranging from 6.2 to 16.7 months. The complex interactions between the tumor and the cells of tumor microenvironment leads to tumor evolution which ultimately results in treatment failure. Immunotherapy has shown great potential in the treatment of solid tumors but has been less effective in treating glioblastoma. Failure of immunotherapy in glioblastoma has been attributed to low T-cell infiltration in glioblastoma and dysfunction of the T-cells that are present in the glioblastoma microenvironment. Recent advances in single-cell sequencing have increased our understanding of the transcriptional changes in the tumor microenvironment pre and post-treatment. Another treatment modality targeting the tumor microenvironment that has failed in glioblastoma has been anti-angiogenic therapy such as the VEGF neutralizing antibody bevacizumab, which did not improve survival in randomized clinical trials. Interestingly, the immunosuppressed microenvironment and abnormal vasculature of glioblastoma interact in ways that suggest the potential for synergy between these two therapeutic modalities that have failed individually. Abnormal tumor vasculature has been associated with immune evasion and the creation of an immunosuppressive microenvironment, suggesting that inhibiting pro-angiogenic factors like VEGF can increase infiltration of effector immune cells into the tumor microenvironment. Remodeling of the tumor vasculature by inhibiting VEGFR2 has also been shown to improve the efficacy of PDL1 cancer immunotherapy in mouse models of different cancers. In this review, we discuss the recent developments in our understanding of the glioblastoma tumor microenvironment specially the tumor vasculature and its interactions with the immune cells, and opportunities to target these interactions therapeutically. Combining anti-angiogenic and immunotherapy in glioblastoma has the potential to unlock these therapeutic modalities and impact the survival of patients with this devastating cancer.
| S-EPMC8790087 | biostudies-literature
Project description:BACKGROUND:Glioblastoma multiform (GBM) is a devastating brain tumor with maximum surgical resection, radiotherapy plus concomitant and adjuvant temozolomide (TMZ) as the standard treatment. Diverse clinicopathological and molecular features are major obstacles to accurate predict survival and evaluate the efficacy of chemotherapy or radiotherapy. Reliable prognostic biomarkers are urgently needed for postoperative GBM patients. METHODS:The protein coding genes (PCGs) and long non-coding RNA (lncRNA) gene expression profiles of 233 GBM postoperative patients were obtained from The Cancer Genome Atlas (TCGA), TANRIC and Gene Expression Omnibus (GEO) database. We randomly divided the TCGA set into a training (n = 76) and a test set (n = 77) and used GSE7696 (n = 80) as an independent validation set. Survival analysis and the random survival forest algorithm were performed to screen survival associated signature. RESULTS:Six PCGs (EIF2AK3, EPRS, GALE, GUCY2C, MTHFD2, RNF212) and five lncRNAs (CTD-2140B24.6, LINC02015, AC068888.1, CERNA1, LINC00618) were screened out by a risk score model and formed a PCG-lncRNA signature for its predictive power was strongest (AUC = 0.78 in the training dataset). The PCG-lncRNA signature could divide patients into high- risk or low-risk group with significantly different survival (median 7.47 vs. 18.27 months, log-rank test P < 0.001) in the training dataset. Similar result was observed in the test dataset (median 11.40 vs. 16.80 months, log-rank test P = 0.001) and the independent set (median 8.93 vs. 16.22 months, log-rank test P = 0.007). Multivariable Cox regression analysis verified that it was an independent prognostic factor for the postsurgical patients with GBM. Compared with IDH mutation status, O-(6)-methylguanine DNA methyltransferase promoter methylation status and age, the signature was proved to have a superior predictive power. And stratified analysis found that the signature could further separated postoperative GBM patients who received TMZ-chemoradiation into high- and low-risk groups in TCGA and GEO dataset. CONCLUSIONS:The PCG-lncRNA signature was a novel prognostic marker to predict survival and TMZ-chemoradiation response in GBM patients after surgery.
| S-EPMC6302404 | biostudies-literature