Evidence map›Paper›PMID 34301218›Full record

ArticleBMC cancer2021

Integration of RNA-Seq and proteomics data identifies glioblastoma multiforme surfaceome signature.

Saiful Effendi Syafruddin, Wan Fahmi Wan Mohamad Nazarie, Nurshahirah Ashikin Moidu, Bee Hong Soon, M Aiman Mohtar

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
4.2field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 35 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Saiful Effendi SyafruddinUKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Cheras, 56000, Kuala Lumpur, Malaysia.
Wan Fahmi Wan Mohamad NazarieFaculty of Science and Natural Resources, Universiti Malaysia Sabah, 88400, Kota Kinabalu, Sabah, Malaysia.
Nurshahirah Ashikin MoiduUKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Cheras, 56000, Kuala Lumpur, Malaysia.
Bee Hong SoonDepartment of Surgery, Neurosurgery Division, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Cheras, 56000, Kuala Lumpur, Malaysia.
M Aiman MohtarUKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Cheras, 56000, Kuala Lumpur, Malaysia. m.aimanmohtar@ppukm.ukm.edu.my.ORCID http://orcid.org/0000-0002-9015-9802
University Kebangsaan Malaysia Medical Centre · MYNational University of Malaysia · MYUniversiti of Malaysia Sabah · MY

Funding

Fundamental Research Grant Scheme FRGS/1/2018/STG04/UKM/03/1International Centre for Genetic Engineering and Biotechnology CRP/MYS19-04_EC
6 · The paper itself

Abstract

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.

Indexed as

Biomarkers, TumorProteomeTranscriptomeBrain NeoplasmsComputational BiologyFemaleGene Expression ProfilingGlioblastomaHumansMaleNeoplasm StagingProtein Interaction MappingProtein Interaction MapsProteomicsSignal TransductionBiomarkers, TumorProteomeCell surface proteinsDifferentially expressed genesGTExNetwork analysisProtein-protein interactionTCGA

Identifiers

PMID34301218
PMCPMC8306276
OpenAlexW3179907307

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.