MétaCan
Menu
Back to cohort
Record W4394768055 · doi:10.1186/s12885-024-11914-6

Integrated transcriptomics uncovers an enhanced association between the prion protein gene expression and vesicle dynamics signatures in glioblastomas

2024· article· en· W4394768055 on OpenAlexaff
Jacqueline Marcia Boccacino, Rafael dos Santos Peixoto, Camila Felix de Lima Fernandes, Giovanni Cangiano, Paula R. Sola, Bárbara Paranhos Coelho, Mariana Brandão Prado, Maria Isabel Melo-Escobar, Breno Pereira de Sousa, Shamini Ayyadhury, Gary D. Bader, Sueli Mieko Oba‐Shinjo, Suely Kazue Nagahashi Marie, Edroaldo Lummertz da Rocha, Marilene H. Lopes

Bibliographic record

VenueBMC Cancer · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersInstituto SerrapilheiraFundação de Amparo à Pesquisa e Inovação do Estado de Santa CatarinaConselho Nacional de Desenvolvimento Científico e TecnológicoFaculdade de Medicina da Universidade de São PauloFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsPRNPBiologyTranscriptomeContext (archaeology)ProteomeGeneProteomicsComputational biologyRNACancer researchGene expressionCell biologyGeneticsGenotype

Abstract

fetched live from OpenAlex

Abstract Background Glioblastoma (GBM) is an aggressive brain tumor that exhibits resistance to current treatment, making the identification of novel therapeutic targets essential. In this context, cellular prion protein (PrP C ) stands out as a potential candidate for new therapies. Encoded by the PRNP gene, PrP C can present increased expression levels in GBM, impacting cell proliferation, growth, migration, invasion and stemness. Nevertheless, the exact molecular mechanisms through which PRNP /PrP C modulates key aspects of GBM biology remain elusive. Methods To elucidate the implications of PRNP /PrP C in the biology of this cancer, we analyzed publicly available RNA sequencing (RNA-seq) data of patient-derived GBMs from four independent studies. First, we ranked samples profiled by bulk RNA-seq as PRNP high and PRNP low and compared their transcriptomic landscape. Then, we analyzed PRNP + and PRNP - GBM cells profiled by single-cell RNA-seq to further understand the molecular context within which PRNP /PrP C might function in this tumor. We explored an additional proteomics dataset, applying similar comparative approaches, to corroborate our findings. Results Functional profiling revealed that vesicular dynamics signatures are strongly correlated with PRNP /PrP C levels in GBM. We found a panel of 73 genes, enriched in vesicle-related pathways, whose expression levels are increased in PRNP high / PRNP + cells across all RNA-seq datasets. Vesicle-associated genes, ANXA1 , RAB31 , DSTN and SYPL1, were found to be upregulated in vitro in an in-house collection of patient-derived GBM. Moreover, proteome analysis of patient-derived samples reinforces the findings of enhanced vesicle biogenesis, processing and trafficking in PRNP high / PRNP + GBM cells. Conclusions Together, our findings shed light on a novel role for PrP C as a potential modulator of vesicle biology in GBM, which is pivotal for intercellular communication and cancer maintenance. We also introduce GBMdiscovery, a novel user-friendly tool that allows the investigation of specific genes in GBM biology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.271
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueBMC CancerSame topicRNA Research and SplicingFrench-language works237,207