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pmid:35049227

A novel risk signature with 6 RNA binding proteins for prognosis prediction in patients with glioblastoma.

Qian-Rong Huang · Jian-Wen Li · Xin-Bin Pan

Medicine · 2021 doi:10.1097/MD.0000000000028065

Paper

complete

Experiment

complete

Data

partial

Analysis

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Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:35049227
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science-record
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2026-11-01T17:36:46Z
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2026-11-01T22:05:37Z
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paper object · 10 fields
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title
A novel risk signature with 6 RNA binding proteins for prognosis prediction in patients with glioblastoma.
doi
10.1097/MD.0000000000028065
pmid
35049227
authors array · 3 items
[0]
Qian-Rong Huang
[1]
Jian-Wen Li
[2]
Xin-Bin Pan
journal
Medicine
year
2021
abstract
ABSTRACT: Recent studies suggested that RNA binding proteins (RBPs) were related to the tumorigenesis and progression of glioma. This study was conducted to identify prognostic RBPs of glioblastoma (GBM) and construct an RBP signature to predict the prognosis of GBM.Univariate Cox regression analysis was carried out to identify the RBPs associated with overall survival of GBM in the The Cancer Genome Atlas (TCGA), GSE16011, and Repository for Molecular Brain Neoplasia data (Rembrandt) datasets, respectively. Overlapping RBPs from the TCGA, GSE16011, and Rembrandt datasets were selected. The biological role of prognostic RBPs was assessed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction analyses. Least absolute shrinkage and selection operator regression analysis and multivariate Cox regression analysis were used to construct an RBP-related risk signature. The prognostic value of RBP signature was measured by Kaplan-Meier method and time-dependent receiver operating characteristic curve. A nomogram based on independent prognostic factors was established to predict survival for GBM. The CGGA cohort was used as the validation cohort for external validation.This study identified 27 RBPs associated with the prognosis of GBM and constructed a 6-RPBs signature. Kaplan-Meier curves suggested that high-risk score was associated with a poor prognosis. Area under the curve of 1-, 3-, and 5-year overall survival was 0.618, 0.728, and 0.833 for TCGA cohort, 0.655, 0.909, and 0.911 for GSE16011 cohort, and 0.665, 0.792, and 0.781 for Rembrandt cohort, respectively. A nomogram with 4 parameters (age, chemotherapy, O6-methylguanine-DNA methyltransferase promoter status, and risk score) was constructed. The calibration curve showed that the nomogram prediction was in good agreement with the actual observation.The 6-RBPs signature could effectively predict the prognosis of GBM, and our findings supplemented the prognostic index of GBM to a certain extent.
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Univariate Cox regression analysis was used to select prognostic-related RBPs in the TCGA, GSE16011, and Rembrandt datasets, respectively, with P value <.05 being the threshold of significance.
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sections[4] "Identification of prognostic-related RBPs in GBM" paragraph 2
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Univariate Cox regression analysis was used to select prognostic-related RBPs in the TCGA, GSE16011, and Rembrandt datasets, respectively, with P value <.05 being the threshold of significance.
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sections[18] "Footnotes" paragraph 2
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The datasets generated during and/or analyzed during the present study are publicly available.
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This study identified 27 RBPs associated with the prognosis of GBM and constructed a 6-RPBs signature.
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This study identified 27 RBPs associated with the prognosis of GBM and constructed a 6-RPBs signature.
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This study identified 27 RBPs associated with the prognosis of GBM and constructed a 6-RPBs signature.
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Intrinsic Gene Expression Profiles of Gliomas are a Better Predictor of Survival than Histology
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method.reader_differs_from_extractor
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review.human_critique
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review.independent_reader
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review.machine_critique
assays array · 1 item
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f2132e96ae6c7a4e
required_operations array · 1 item
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cox_ph
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
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Univariate Cox regression analysis was used to select prognostic-related RBPs in the TCGA, GSE16011, and Rembrandt datasets, respectively, with P value <.05 being the threshold of significance.
order_basis
analysis_only
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assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35049227", "kind": "science-record", "revision": 4, "content_hash": "sha256:298a508c880e201450513f8797e03a1f31c08fe870ff578274e53f2c0ba37db5", "created_at": "2026-11-01T17:36:46Z", "updated_at": "2026-11-01T22:05:37Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A novel risk signature with 6 RNA binding proteins for prognosis prediction in patients with glioblastoma.", "doi": "10.1097/MD.0000000000028065", "pmid": "35049227", "authors": ["Qian-Rong Huang", "Jian-Wen Li", "Xin-Bin Pan"], "journal": "Medicine", "year": 2021, "abstract": "ABSTRACT: Recent studies suggested that RNA binding proteins (RBPs) were related to the tumorigenesis and progression of glioma. This study was conducted to identify prognostic RBPs of glioblastoma (GBM) and construct an RBP signature to predict the prognosis of GBM.Univariate Cox regression analysis was carried out to identify the RBPs associated with overall survival of GBM in the The Cancer Genome Atlas (TCGA), GSE16011, and Repository for Molecular Brain Neoplasia data (Rembrandt) datasets, respectively. Overlapping RBPs from the TCGA, GSE16011, and Rembrandt datasets were selected. The biological role of prognostic RBPs was assessed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction analyses. Least absolute shrinkage and selection operator regression analysis and multivariate Cox regression analysis were used to construct an RBP-related risk signature. The prognostic value of RBP signature was measured by Kaplan-Meier method and time-dependent receiver operating characteristic curve. A nomogram based on independent prognostic factors was established to predict survival for GBM. The CGGA cohort was used as the validation cohort for external validation.This study identified 27 RBPs associated with the prognosis of GBM and constructed a 6-RPBs signature. Kaplan-Meier curves suggested that high-risk score was associated with a poor prognosis. Area under the curve of 1-, 3-, and 5-year overall survival was 0.618, 0.728, and 0.833 for TCGA cohort, 0.655, 0.909, and 0.911 for GSE16011 cohort, and 0.665, 0.792, and 0.781 for Rembrandt cohort, respectively. A nomogram with 4 parameters (age, chemotherapy, O6-methylguanine-DNA methyltransferase promoter status, and risk score) was constructed. The calibration curve showed that the nomogram prediction was in good agreement with the actual observation.The 6-RBPs signature could effectively predict the prognosis of GBM, and our findings supplemented the prognostic index of GBM to a certain extent.", "claims": [{"id": "claim-method", "statement": "Univariate Cox regression analysis was used to select prognostic-related RBPs in the TCGA, GSE16011, and Rembrandt datasets, respectively, with P value <.05 being the threshold of significance.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35049227", "locator": "sections[4] \"Identification of prognostic-related RBPs in GBM\" paragraph 2", "quote": "Univariate Cox regression analysis was used to select prognostic-related RBPs in the TCGA, GSE16011, and Rembrandt datasets, respectively, with P value <.05 being the threshold of significance."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated during and/or analyzed during the present study are publicly available.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35049227", "locator": "sections[18] \"Footnotes\" paragraph 2", "quote": "The datasets generated during and/or analyzed during the present study are publicly available."}], "state": "complete"}, {"id": "claim-target-result", "statement": "This study identified 27 RBPs associated with the prognosis of GBM and constructed a 6-RPBs signature.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35049227", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "This study identified 27 RBPs associated with the prognosis of GBM and constructed a 6-RPBs signature."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "This study identified 27 RBPs associated with the prognosis of GBM and constructed a 6-RPBs signature.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35049227"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE16011"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE16011"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35049227", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1097/MD.0000000000028065", "sha256": 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