Dataset Information

Proteo-transcriptomics meta-analysis identifies SUMO2 as a promising target in glioblastoma multiforme therapeutics

ABSTRACT:

Background

Glioblastoma multiforme (GBM) is a deadly brain tumour with minimal survival rates due to the ever-expanding heterogeneity, chemo and radioresistance. Kinases are known to crucially drive GBM pathology; however, a rationale therapeutic combination that can simultaneously inhibit multiple kinases has not yet emerged successfully.

Results

Here, we analyzed the GBM patient data from several publicly available repositories and deduced hub GBM kinases, most of which were identified to be SUMOylated by SUMO2/3 isoforms. Not only the hub kinases but a significant proportion of GBM upregulated genes involved in proliferation, metastasis, invasion, epithelial-mesenchymal transition, stemness, DNA repair, stromal and macrophages maintenance were also identified to be the targets of SUMO2 isoform. Correlatively, high expression of SUMO2 isoform was found to be significantly associated with poor patient survival.

Conclusions

Although many natural products and drugs are evidenced to target general SUMOylation, however, our meta-analysis strongly calls for the need to design SUMO2/3 or even better SUMO2 specific inhibitors and also explore the SUMO2 transcription inhibitors for universally potential, physiologically non-toxic anti-GBM drug therapy.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02279-y. Highlights The major highlights of this study are as follows: Key upregulated hub kinases and coding genes in GBM are found to be targets of SUMO2 conjugation. SUMO2 is significantly expressed in adult primary and recurrent GBMs as well as in pediatric GBM tumours. Orthotropic xenografts from adult and pediatric GBMs confirm high expression of SUMO2 in GBM tumour samples. SUMO2 is significantly associated with patient survival plot and pan-cancer cell fitness. Rationale design of SUMO2 inhibitors or search for its transcriptional inhibitors is urgently required through industry-academia collaboration for an anti-GBM and potentially pan-cancer therapeutics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02279-y.

SUBMITTER: Krishna A

PROVIDER: S-EPMC8555349 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Anaplastic astrocytoma (AA) and its more aggressive counterpart, glioblastoma multiforme (GBM), are the most common intrinsic brain tumors in adults and are almost universally fatal. A deeper understanding of the molecular relationship of these tumor types is necessary to derive insights into the diagnosis, prognosis, and treatment of gliomas. Although genomewide profiling of expression levels with microarrays can be used to identify differentially expressed genes between these tumor types, comparative studies so far have resulted in gene lists that show little overlap.To achieve a more accurate and stable list of the differentially expressed genes and pathways between primary GBM and AA, we performed a meta-analysis using publicly available genome-scale mRNA data sets. There were four data sets with sufficiently large sample sizes of both GBMs and AAs, all of which coincidentally used human U133 platforms from Affymetrix, allowing for easier and more precise integration of data. After scoring genes and pathways within each data set, we combined the statistics across studies using the nonparametric rank sum method to identify the features that differentiate GBMs and AAs. We found >900 statistically significant probe sets after correction for multiple testing from the >22,000 tested. We also used the rank sum approach to select >20 significant Biocarta pathways after correction for multiple testing out of >175 pathways examined. The most significant pathway was the hypoxia-inducible factor (HIF) pathway. Our analysis suggests that many of the most statistically significant genes work together in a HIF1A/VEGF-regulated network to increase angiogenesis and invasion in GBM when compared to AA.We have performed a meta-analysis of genome-scale mRNA expression data for 289 human malignant gliomas and have identified a list of >900 probe sets and >20 pathways that are significantly different between GBM and AA. These feature lists could be utilized to aid in diagnosis, prognosis, and grade reduction of high-grade gliomas and to identify genes that were not previously suspected of playing an important role in glioma biology. More generally, this approach suggests that combined analysis of existing data sets can reveal new insights and that the large amount of publicly available cancer data sets should be further utilized in a similar manner.

Project description:BackgroundGlioblastoma multiforme is a malignant intracranial neoplasm that constitutes a therapeutic challenge because of the associated high morbidity and mortality given the lack of effective approved medication and aggressive nature of the tumor. However, there has been extensive research recently to address the reasons implicated in the resistant nature of the tumor to pharmaceutical compounds, which have resulted in several clinical trials investigating promising treatment approaches.MethodsWe reviewed literature published since 2010 from PUBMED and several annual meeting abstracts through 15 September 2020. Selected articles included those relevant to topics of glioblastoma tumor biology, original basic research, clinical trials, seminal reviews, and meta-analyses. We provide a discussion based on the collected evidence regarding the challenging factors encountered during treatment, and we highlighted the relevant trials of novel therapies including immunotherapy and targeted medication.ResultsSelected literature revealed four main factors implicated in the low efficacy encountered with investigational treatments which included: (1) blood-brain barrier; (2) immunosuppressive microenvironment; (3) genetic heterogeneity; (4) external factors related to previous systemic treatment that can modulate tumor microenvironment. Investigational therapies discussed in this review were classified as immunotherapy and targeted therapy. Immunotherapy included: (1) immune checkpoint inhibitors; (2) adoptive cell transfer therapy; (3) therapeutic vaccines; (4) oncolytic virus therapy. Targeted therapy included tyrosine kinase inhibitors and other receptor inhibitors. Finally, we provide our perspective on future directions in treatment of glioblastoma.ConclusionDespite the limited success in development of effective therapeutics in glioblastoma, many treatment approaches hold potential promise including immunotherapy and novel combinational drugs. Addressing the molecular landscape and resistant immunosuppressive nature of glioblastoma are imperative in further development of effective treatments.

Project description:BackgroundGlioblastoma multiforme (GBM) is a highly lethal, stage IV brain tumour with a prevalence of approximately 2 per 10,000 people globally. The cell surface proteins or surfaceome serve as information gateway in many oncogenic signalling pathways and are important in modulating cancer phenotypes. Dysregulation in surfaceome expression and activity have been shown to promote tumorigenesis. The expression of GBM surfaceome is a case in point; OMICS screening in a cell-based system identified that this sub-proteome is largely perturbed in GBM. Additionally, since these cell surface proteins have 'direct' access to drugs, they are appealing targets for cancer therapy. However, a comprehensive GBM surfaceome landscape has not been fully defined yet. Thus, this study aimed to define GBM-associated surfaceome genes and identify key cell-surface genes that could potentially be developed as novel GBM biomarkers for therapeutic purposes.MethodsWe integrated the RNA-Seq data from TCGA GBM (n = 166) and GTEx normal brain cortex (n = 408) databases to identify the significantly dysregulated surfaceome in GBM. This was followed by an integrative analysis that combines transcriptomics, proteomics and protein-protein interaction network data to prioritize the high-confidence GBM surfaceome signature.ResultsOf the 2381 significantly dysregulated genes in GBM, 395 genes were classified as surfaceome. Via the integrative analysis, we identified 6 high-confidence GBM molecular signature, HLA-DRA, CD44, SLC1A5, EGFR, ITGB2, PTPRJ, which were significantly upregulated in GBM. The expression of these genes was validated in an independent transcriptomics database, which confirmed their upregulated expression in GBM. Importantly, high expression of CD44, PTPRJ and HLA-DRA is significantly associated with poor disease-free survival. Last, using the Drugbank database, we identified several clinically-approved drugs targeting the GBM molecular signature suggesting potential drug repurposing.ConclusionsIn summary, we identified and highlighted the key GBM surface-enriched repertoires that could be biologically relevant in supporting GBM pathogenesis. These genes could be further interrogated experimentally in future studies that could lead to efficient diagnostic/prognostic markers or potential treatment options for GBM.

Dataset Information

Proteo-transcriptomics meta-analysis identifies SUMO2 as a promising target in glioblastoma multiforme therapeutics

Background

Results

Conclusions

Graphical Abstract

Supplementary Information

Supplementary Information

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