Glioblastoma multiforme: a multi-omics analysis of driver genes and tumour heterogeneity

Herrera-Oropeza, Gabriel Emilio; Angulo-Rojo, Carla; Gástelum-López, Santos Alberto; Varela‐Echavarría, Alfredo; Hernández-Rosales, Maribel; Aviña-Padilla, Katia

doi:10.1098/rsfs.2020.0072

Cited by 20 publications

(16 citation statements)

References 96 publications

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“…Cell surface vimentin on the GBM has been shown to initiate tumors in the adjacent cells, and two monoclonal antibodies 86C and pritumumab were successful to target cell surface vimentin offering promising treatment options to GBM ( Noh et al, 2016 ; Babic et al, 2018 ). VIM was seen upregulated in the classical and mesenchymal subtypes and evidently the transitions from classical to mesenchymal GBM were correlated to higher expressions of VIM ( Schiffer et al, 1986 ; Herrera-Oropeza et al, 2021 ). Upregulation of vimentin protein was evident in the proliferation and migration of GBM.…”

Section: Discussionmentioning

confidence: 92%

“…It was found upregulated in mesenchymal and classical subtypes ( Delany et al, 2008 ) due to which the overall survival rate of SPARC was just 7 months and disease-free survival was 2.2 median months. Similar to VIM , although SPARC was remarkably overexpressed in most cancer types, a ten-fold increased expression seen in GBM makes it crucial ( Liu & Lathia, 2016 ); ( Yao et al, 2014 ); ( Herrera-Oropeza et al, 2021 ). The fact that the expression of DDN and SH3GL2 were attributed to the proneural subtype makes them strong prognostic GBM biomarker candidates.…”

Section: Discussionmentioning

confidence: 99%

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Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates

Aishwarya²,

et al. 2022

Front. Genet.

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Glioblastoma is an aggressive malignant tumor of the brain and spinal cord. Due to the blood–brain barrier, the accessibility of its treatments still remains significantly challenging. Unfortunately, the recurrence rates of glioblastoma upon surgery are very high too. Hence, understanding the molecular drivers of disease progression is valuable. In this study, we aimed to investigate the molecular drivers responsible for glioblastoma progression and identify valid biomarkers. Three microarray expression profiles GSE90604, GSE50601, and GSE134470 containing healthy and glioblastoma-affected samples revealed overlapping differentially expressed genes (DEGs). The interrelational pathway enrichment analysis elucidated the halt of cell cycle checkpoints and activation of signaling pathways and led to the identification of 6 predominant hub genes. Validation of hub genes in comparison with The Cancer Genome Atlas datasets identified the potential biomarkers of glioblastoma. The study evaluated two significantly upregulated genes, SPARC (secreted protein acidic and rich in cysteine) and VIM (vimentin) for glioblastoma. The genes CACNA1E (calcium voltage-gated channel subunit alpha1 e), SH3GL2 (SH3 domain-containing GRB2-like 2, endophilin A1), and DDN (dendrin) were identified as under-expressed genes as compared to the normal and pan-cancer tissues along with prominent putative prognostic biomarker potentials. The genes DDN and SH3GL2 were found to be upregulated in the proneural subtype, while CACNA1E in the mesenchymal subtype of glioblastoma exhibits good prognostic potential. The mutational analysis also revealed the benign, possibly, and probably damaging substitution mutations. The correlation between the DEG and survival in glioblastoma was evaluated using the Kaplan–Meier plots, and VIM had a greater life expectancy of 60.25 months. Overall, this study identified key candidate genes that might serve as predictive biomarkers for glioblastoma.

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Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates

Aishwarya²,

et al. 2022

Front. Genet.

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“…This biological behavior could be due to tumor’s cellular origin and heterogeneity [28], and tissue-specific expression [2, 8]. Due to their remarkable heterogeneity, glioblastoma, prostate, and kidney tumors were found with a less representative shared behavior in the upregulation of IGs.…”

Section: Discussionmentioning

confidence: 99%

Deciphering the tissue-specific regulatory role of intronless genes across cancers

Aviña-Padilla¹,

Ramírez-Rafael²,

Herrera-Oropeza

et al. 2022

Preprint

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Intronless genes (IGs) or single-exon genes lacking an intron are found across most Eukaryotes. Notably, IGs display a higher transcriptional fidelity as they are not regulated through alternative splicing, suggesting better predictability biomarkers and easier regulation as targets for therapy. Cancer is a complex disease that relies on progressive uncontrolled cell division linked with multiple dysfunctional biological processes. Tumor heterogeneity remains the most challenging feature in cancer diagnosis and treatment. Given the clinical relevance of IGs, we aim to identify their unique expression profiles and interactome, that may act as functional signatures across eight different cancers. We identified 940 protein-coding IGs in the human genome, of which about 35% were differentially expressed across the analyzed cancer datasets. Specifically, ∼78% of differentially expressed IGs were undergoing transcriptional reprogramming with elevated expression in tumor cells. Remarkably, in all the studied tumors, a highly conserved induction of a group of deacetylase-histones located in a region of chromosome 6 enriched in nucleosome and chromatin condensation processes. This study highlights that differentially expressed human intronless genes across cancer types are prevalent in epigenetic regulatory roles participating in specific PPI networks for ESCA, GBM, and LUAD tumors. We determine that IGs play a key role in the tumor phenotype at transcriptional and post-transcriptional levels, with important mechanisms such as interactomics rewiring.

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“…A recent study highlighted the importance of GBM heterogeneity, which makes this kind of cancer among the most challenging to treat ( 5 ). The different patterns of heterogeneity in glioma show different chromosome, genome, and transcriptome characteristics ( 5 ) and different patterns of biomarkers and driver genes ( 6 ). Based on these characteristics, we can obtain different effective and detailed targets for different biological models of GBM.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Different Subtypes of Immune Cell Infiltration in Glioblastoma to Aid Immunotherapy

Feng

et al. 2022

Front. Immunol.

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Glioblastoma multiforme (GBM) has been identified as a frequently occurring adult primary brain cancer that is highly aggressive. Currently, the prognostic outcome for GBM patients is dismal, even with intensive treatment, and the median overall survival (OS) is 14.6 months. Immunotherapy, which is specific at the cellular level and can generate persistent immunosurveillance, is now becoming a promising tool to treat diverse cancers. However, the complicated nature of the tumor microenvironment (TME) makes it challenging to develop anti-GBM immunotherapy because several cell types, cytokines, and signaling pathways are involved in generating the immunosuppressive environment. Novel immunotherapies can illustrate novel tumor-induced immunosuppressive mechanisms. Here, we used unsupervised clustering analysis to identify different subtypes of immune cell infiltration that actuated different prognoses, biological actions, and immunotherapy responses. Gene cluster A, with a hot immune cell infiltration phenotype, had high levels of immune-related genes (IRGs), which were associated with immune pathways including the interferon-gamma response and interferon-alpha response, and had low IDH1 and ATRX mutation frequencies. Gene cluster B, a cold immune cell infiltration subtype, exhibited a high expression of the KCNIP2, SCRT1, CPLX2, JPH3, UNC13A, GABRB3, ARPP21, DLGAP1, NRXN1, DLL3, CA10, MAP2, SEZ6L, GRIA2, and GRIA4 genes and a low expression of immune-related genes, i.e., low levels of immune reactivity. Our study highlighted the complex interplay between immune cell infiltration and genetic mutation in the establishment of the tumor immune phenotype. Gene cluster A was identified as an important subtype with a better prognosis and improved immunotherapy response.

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Glioblastoma multiforme: a multi-omics analysis of driver genes and tumour heterogeneity

Cited by 20 publications

References 96 publications

Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates

Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates

Deciphering the tissue-specific regulatory role of intronless genes across cancers

Characterization of Different Subtypes of Immune Cell Infiltration in Glioblastoma to Aid Immunotherapy

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