The proteomic landscape of glioma stem-like cells

The translatome of glioblastoma

Glioblastoma (GB), the most common and aggressive brain tumor, demonstrates intrinsic resistance to current therapies, resulting in poor clinical outcomes. Cancer progression can be partially attributed to the deregulation of protein translation mechanisms that drive cancer cell growth. In this study, we present the translatome landscape of GB as a valuable data resource. Eight patient-derived GB sphere cultures (GSCs) were analyzed using ribosome profiling and messenger RNA (mRNA) sequencing. We investigated inter-cell-line differences through differential expression analysis at both the translatome and transcriptome levels. Translational changes post-radiotherapy were assessed at 30 and 60 min. The translation of non-coding RNAs (ncRNAs) was validated using in-house and public mass spectrometry (MS) data, whereas RNA expression was confirmed by quantitative PCR (qPCR). Our findings demonstrate that ribosome sequencing provides more detailed information than MS or transcriptional analyses. Transcriptional similarities among GSCs correlate with translational similarities, aligning with previously defined subtypes such as proneural and mesenchymal. Additionally, we identified a broad spectrum of open reading frame types in both coding and non-coding mRNA regions, including long non-coding RNAs (lncRNAs) and pseudogenes undergoing active translation. Translation of ncRNAs into peptides was independently confirmed by in-house data and external MS data. We also observed that translational regulation of histones (downregulated) and splicing factors (upregulated) occurs in response to radiotherapy. These data offer new insights into genome-wide protein synthesis, identifying translationally regulated genes and alternative translation initiation sites in GB under normal and radiotherapeutic conditions, providing a rich resource for GB research. Further functional validation of differentially expressed genes after radiotherapy is needed. Understanding translational control in GB can reveal mechanistic insights and identify currently unknown biomarkers, ultimately enhancing the diagnosis and treatment of this aggressive brain cancer.

An overview of glioblastoma multiforme and temozolomide resistance: can LC-MS-based proteomics reveal the fundamental mechanism of temozolomide resistance?

Glioblastoma multiforme (GBM) is a primary type of lethal brain tumor. Over the last two decades, temozolomide (TMZ) has remained the primary chemotherapy for GBM. However, TMZ resistance in GBM constitutes an underlying factor contributing to high rates of mortality. Despite intense efforts to understand the mechanisms of therapeutic resistance, there is currently a poor understanding of the molecular processes of drug resistance. For TMZ, several mechanisms linked to therapeutic resistance have been proposed. In the past decade, significant progress in the field of mass spectrometry-based proteomics has been made. This review article discusses the molecular drivers of GBM, within the context of TMZ resistance with a particular emphasis on the potential benefits and insights of using global proteomic techniques.

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

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.

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.

Identification-Free Control over the Precursor Isotopic Mass Misassignment in Orbitrap-Based Proteomics

Selection of a precursor ion from a peptide isotopic cluster to obtain a fragmentation mass spectrum is a crucial step in data-dependent proteome analysis. However, the monoisotopic mass assignment performed in this step is often an issue confronted by the data acquisition software of hybrid Orbitrap FTMS that is most widely used in proteomics. To address the problem, many data processing tools, such as raw data converters and search engines, have optional accounting for the precursor mass shift due to the isotopic error. These solutions require additional data preprocessing steps and lead to an increase in the search space, thus making the analysis longer and/or less reliable. In this work, we processed 100 Orbitrap-based LC-MS/MS runs from 10 publicly available data sets to examine the rate of precursor isotope misassignment. The effect from taking the isotope error into account during the search on the number of identified peptides varied in a wide range from 0 to 33%. Thus, it may be tempting to spend extra time before or during a search to account for the mass assignment issue. Alternatively, this effect can be predicted a priori using an identification-free metric, which can be a part of data quality control software. Based on the results obtained in this work, we propose such a metric be further added into the visual and intuitive quality control software, viQC, developed previously and available at https://github.com/lisavetasol/viQC. It takes about a minute to calculate and plot nine quality metrics, including the proposed one for typical proteome analysis.

Role of MEK partner-1 in cancer stemness through MEK/ERK pathway in cancerous neural stem cells, expressing EGFRviii

Background

Glioma stem cells (GSCs) are a major cause of the frequent relapse observed in glioma, due to their high drug resistance and their differentiation potential. Therefore, understanding the molecular mechanisms governing the ‘cancer stemness’ of GSCs will be particularly important for improving the prognosis of glioma patients.

Methods

We previously established cancerous neural stem cells (CNSCs) from immortalized human neural stem cells (F3 cells), using the H-Ras oncogene. In this study, we utilized the EGFRviii mutation, which frequently occurs in brain cancers, to establish another CNSC line (F3.EGFRviii), and characterized its stemness under spheroid culture.

Results

The F3.EGFRviii cell line was highly tumorigenic in vitro and showed high ERK1/2 activity as well as expression of a variety of genes associated with cancer stemness, such as SOX2 and NANOG, under spheroid culture conditions. Through meta-analysis, PCR super-array, and subsequent biochemical assays, the induction of MEK partner-1 (MP1, encoded by the LAMTOR3 gene) was shown to play an important role in maintaining ERK1/2 activity during the acquisition of cancer stemness under spheroid culture conditions. High expression of this gene was also closely associated with poor prognosis in brain cancer.

Conclusion

These data suggest that MP1 contributes to cancer stemness in EGFRviii-expressing glioma cells by driving ERK activity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12943-017-0703-y) contains supplementary material, which is available to authorized users.