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pmid:27677590

Classifying lower grade glioma cases according to whole genome gene expression.

Baoshi Chen · Tingyu Liang · Pei Yang · Haoyuan Wang · Yanwei Liu · Fan Yang · Gan You

Oncotarget · 2016 doi:10.18632/oncotarget.12188

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Experiment

complete

Data

partial

Analysis

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Execution

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Classifying lower grade glioma cases according to whole genome gene expression.
doi
10.18632/oncotarget.12188
pmid
27677590
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[0]
Baoshi Chen
[1]
Tingyu Liang
[2]
Pei Yang
[3]
Haoyuan Wang
[4]
Yanwei Liu
[5]
Fan Yang
[6]
Gan You
journal
Oncotarget
year
2016
abstract
OBJECTIVE: To identify a gene-based signature as a novel prognostic model in lower grade gliomas. RESULTS: A gene signature developed from HOXA7, SLC2A4RG and MN1 could segregate patients into low and high risk score groups with different overall survival (OS), and was validated in TCGA RNA-seq and GSE16011 mRNA array datasets. Receiver operating characteristic (ROC) was performed to show that the three-gene signature was more sensitive and specific than histology, grade, age, IDH1 mutation and 1p/19q co-deletion. Gene Set Enrichment Analysis (GSEA) and GO analysis showed high-risk samples were associated with tumor associated macrophages (TAMs) and highly invasive phenotypes. Moreover, HOXA7-siRNA inhibited migration and invasion in vitro, and downregulated MMP9 at the protein level in U251 glioma cells. METHODS: A cohort of 164 glioma specimens from the Chinese Glioma Genome Atlas (CGGA) array database were assessed as the training group. TCGA RNA-seq and GSE16011 mRNA array datasets were used for validation. Regression analyses and linear risk score assessment were performed for the identification of the three-gene signature comprising HOXA7, SLC2A4RG and MN1. CO NCLUSIONS: We established a three-gene signature for lower grade gliomas, which could independently predict overall survival (OS) of lower grade glioma patients with higher sensitivity and specificity compared with other clinical characteristics. These findings indicate that the three-gene signature is a new prognostic model that could provide improved OS prediction and accurate therapies for lower grade glioma patients.
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OS in high- and low-risk patient groups was estimated by the Kaplan-Meier method and 2-sided log-rank test in GraphPad Prism Version 6.01.
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OS in high- and low-risk patient groups was estimated by the Kaplan-Meier method and 2-sided log-rank test in GraphPad Prism Version 6.01.
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A cohort of 164 glioma specimens from the Chinese Glioma Genome Atlas (CGGA) array database were assessed as the training group. Samples were obtained from the Chinese Glioma Genome Atlas (CGGA) dataset (the training set);the TCGA RNA-seq database and GSE16011 array dataset were assessed as independent validation sets. Among the 164 lower grade glioma specimens, 117 grade II and 47 grade III samples were identified.
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A cohort of 164 glioma specimens from the Chinese Glioma Genome Atlas (CGGA) array database were assessed as the training group.
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Samples were obtained from the Chinese Glioma Genome Atlas (CGGA) dataset (the training set);the TCGA RNA-seq database and GSE16011 array dataset were assessed as independent validation sets.
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Among the 164 lower grade glioma specimens, 117 grade II and 47 grade III samples were identified.
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We established a three-gene signature for lower grade gliomas, which could independently predict overall survival (OS) of lower grade glioma patients with higher sensitivity and specificity compared with other clinical characteristics.
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A cohort of 164 glioma specimens from the Chinese Glioma Genome Atlas (CGGA) array database were assessed as the training group. TCGA RNA-seq and GSE16011 mRNA array datasets were used for validation. Regression analyses and linear risk score assessment were performed for the identification of the three-gene signature comprising HOXA7, SLC2A4RG and MN1.
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We established a three-gene signature for lower grade gliomas, which could independently predict overall survival (OS) of lower grade glioma patients with higher sensitivity and specificity compared with other clinical characteristics.
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We established a three-gene signature for lower grade gliomas, which could independently predict overall survival (OS) of lower grade glioma patients with higher sensitivity and specificity compared with other clinical characteristics.
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A cohort of 164 glioma specimens from the Chinese Glioma Genome Atlas (CGGA) array database were assessed as the training group. Samples were obtained from the Chinese Glioma Genome Atlas (CGGA) dataset (the training set);the TCGA RNA-seq database and GSE16011 array dataset were assessed as independent validation sets. Among the 164 lower grade glioma specimens, 117 grade II and 47 grade III samples were identified.
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Intrinsic Gene Expression Profiles of Gliomas are a Better Predictor of Survival than Histology
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[2]
82
[3]
52
[4]
30
[5]
0.001
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[0]
[1]
high
[2]
82
[3]
30
[4]
52
[5]
[23] array · 6 items
[0]
[1]
NA
[2]
0
[3]
[4]
[5]
[24] array · 6 items
[0]
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[1]
MUT
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5
[3]
1
[4]
4
[5]
>0.05
[25] array · 6 items
[0]
[1]
WT
[2]
90
[3]
44
[4]
46
[5]
[26] array · 6 items
[0]
[1]
NA
[2]
69
[3]
[4]
[5]
[27] array · 6 items
[0]
1p/19q co-deletion
[1]
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[2]
32
[3]
16
[4]
16
[5]
1
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[0]
[1]
No
[2]
132
[3]
66
[4]
66
[5]
[29] array · 6 items
[0]
[1]
NA
[2]
0
[3]
[4]
[5]
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[0]
EGFR amp
[1]
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[2]
3
[3]
0
[4]
3
[5]
>0.05
[31] array · 6 items
[0]
[1]
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[2]
161
[3]
82
[4]
79
[5]
[32] array · 6 items
[0]
[1]
NA
[2]
0
[3]
[4]
[5]
[33] array · 6 items
[0]
Pre-operative KPS
[1]
Yes
[2]
45
[3]
26
[4]
19
[5]
>0.05
[34] array · 6 items
[0]
[1]
No
[2]
29
[3]
12
[4]
17
[5]
[35] array · 6 items
[0]
[1]
NA
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90
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Univariate and multivariate Cox analysis in CGGA lower grade glioma samples
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PMC5342033
section_index
5
section_title
Clinical and molecular features of low and high risk lower grade glioma patients
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column_count
9
table object · 8 fields
label
Table 3
caption
Univariate and multivariate Cox analysis in CGGA lower grade glioma samples
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[0] array · 3 items
[0]
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[1]
Univariate
[2]
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[0]
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[1]
95%CL
[2]
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[3]
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[4]
95%CL
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[0]
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[0]
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1.997
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4.309
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2.419
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7.676
[4]
<0.0001
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2.262
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0.751
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6.81
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0.147
[5] array · 9 items
[0]
Risk score
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4.872
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2.419
[3]
9.812
[4]
<0.0001
[5]
2.606
[6]
1.690
[7]
4.018
[8]
<0.0001
[6] array · 9 items
[0]
Preoperative KPS
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0.319
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0.107
[3]
0.952
[4]
0.041
[5]
0.700
[6]
0.200
[7]
2.451
[8]
0.577
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section[5]/table-wrap[2]#T3
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Univariate and multivariate Cox analysis in TCGA lower grade glioma samples
structure object · 5 fields
pmcid
PMC5342033
section_index
5
section_title
Clinical and molecular features of low and high risk lower grade glioma patients
row_count
9
column_count
9
table object · 8 fields
label
Table 4
caption
Univariate and multivariate Cox analysis in TCGA lower grade glioma samples
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[0] array · 3 items
[0]
Clinical factors
[1]
Univatiate
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Multivariate
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[0]
HR
[1]
95%CI
[2]
P
[3]
HR
[4]
95%CI
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P
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[0]
Lower
[1]
Upper
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Upper
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[0]
Age
[1]
4.153
[2]
2.65
[3]
6.507
[4]
<0.0001
[5]
4.330
[6]
2.645
[7]
7.088
[8]
<0.0001
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[0]
IDH1 mutation
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0.344
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0.226
[3]
0.524
[4]
<0.0001
[5]
0.591
[6]
0.376
[7]
0.929
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0.023
[5] array · 9 items
[0]
Gender
[1]
0.98
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0.654
[3]
1.468
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0.921
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[6]
[7]
[8]
[6] array · 9 items
[0]
Grade
[1]
3.220
[2]
2.079
[3]
4.986
[4]
<0.0001
[5]
2.834
[6]
1.726
[7]
4.652
[8]
<0.0001
[7] array · 9 items
[0]
Histology
[1]
0.518
[2]
0.344
[3]
0.78
[4]
0.002
[5]
0.791
[6]
0.511
[7]
1.225
[8]
0.293
[8] array · 9 items
[0]
Risk score
[1]
2.21
[2]
1.46
[3]
3.344
[4]
<0.0001
[5]
3.384
[6]
2.085
[7]
5.492
[8]
<0.0001
locator
section[5]/table-wrap[3]#T4
gaps array · 2 items
[0]
asset:data:geo:GSE16011 not downloaded
[1]
asset:data:geo:GSE16011 licence not read
analysis object · 4 fields
state
complete
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method-1
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survival_analysis
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log_rank_test
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Survival analysis
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logrank_test
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time_to_event_with_censoring
evidence object · 3 fields
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verbatim
quote
OS in high- and low-risk patient groups was estimated by the Kaplan-Meier method and 2-sided log-rank test in GraphPad Prism Version 6.01.
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survival_km
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time_to_event_with_censoring
evidence object · 3 fields
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Kaplan-Meier
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cox_ph
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time_to_event_with_censoring
evidence object · 3 fields
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confusion_counts
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solve_confusion_matrix
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reference_standard_and_test
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0.8
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ROC curve
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capability:computational_analysis
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meta_analysis
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candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
state
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nothing:replicable_now
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logrank_test
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basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: log_rank_test.
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tier
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capability_id
capability:computational_analysis
availability_state
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basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
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tier
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GSE16011
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GSE16011
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A cohort of 164 glioma specimens from the Chinese Glioma Genome Atlas (CGGA) array database were assessed as the training group. Samples were obtained from the Chinese Glioma Genome Atlas (CGGA) dataset (the training set);the TCGA RNA-seq database and GSE16011 array dataset were assessed as independent validation sets. Among the 164 lower grade glioma specimens, 117 grade II and 47 grade III samples were identified.
basis
The paper names GSE16011 in GSE16011 array dataset and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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logrank_test
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source:pmid:27677590
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run_analysis
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highly invasive phenotypes. Moreover, HOXA7-siRNA inhibited migration and invasion in vitro, a
[1]
ified in the long OS group. Cell culture and transfection of HOXA7-siRNA Human glioma U251 cells were
[2]
hased from Genepharma (Shanghai, China), and transfected into U251 cells using Lipofectamine™ 2000 (I
[3]
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able 2; there were more patients (n=12) with Ki67 overexpression in the high-risk group compar
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d with HOXA7-siRNA for 48h before RT-PCR and Western blot assays [27]. SUPPLEMENTARY MATERIALS FIGURE
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:27677590", "kind": "science-record", "revision": 8, "content_hash": "sha256:4b8664ae7e798fede733591d1ffb55d5ed4a1b761c18e2f42f69111142e3b3c5", "created_at": "2026-11-01T15:40:20Z", "updated_at": "2026-11-01T21:59:09Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Classifying lower grade glioma cases according to whole genome gene expression.", "doi": "10.18632/oncotarget.12188", "pmid": "27677590", "authors": ["Baoshi Chen", "Tingyu Liang", "Pei Yang", "Haoyuan Wang", "Yanwei Liu", "Fan Yang", "Gan You"], "journal": "Oncotarget", "year": 2016, "abstract": "OBJECTIVE: To identify a gene-based signature as a novel prognostic model in lower grade gliomas.\nRESULTS: A gene signature developed from HOXA7, SLC2A4RG and MN1 could segregate patients into low and high risk score groups with different overall survival (OS), and was validated in TCGA RNA-seq and GSE16011 mRNA array datasets. Receiver operating characteristic (ROC) was performed to show that the three-gene signature was more sensitive and specific than histology, grade, age, IDH1 mutation and 1p/19q co-deletion. Gene Set Enrichment Analysis (GSEA) and GO analysis showed high-risk samples were associated with tumor associated macrophages (TAMs) and highly invasive phenotypes. Moreover, HOXA7-siRNA inhibited migration and invasion in vitro, and downregulated MMP9 at the protein level in U251 glioma cells.\nMETHODS: A cohort of 164 glioma specimens from the Chinese Glioma Genome Atlas (CGGA) array database were assessed as the training group. TCGA RNA-seq and GSE16011 mRNA array datasets were used for validation. Regression analyses and linear risk score assessment were performed for the identification of the three-gene signature comprising HOXA7, SLC2A4RG and MN1.\nCO NCLUSIONS: We established a three-gene signature for lower grade gliomas, which could independently predict overall survival (OS) of lower grade glioma patients with higher sensitivity and specificity compared with other clinical characteristics. These findings indicate that the three-gene signature is a new prognostic model that could provide improved OS prediction and accurate therapies for lower grade glioma patients.", "claims": [{"id": "claim-method", "statement": "OS in high- and low-risk patient groups was estimated by the Kaplan-Meier method and 2-sided log-rank test in GraphPad Prism Version 6.01.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:27677590", "locator": "sections[16] \"Statistical analyses\" paragraph 5", "quote": "OS in high- and low-risk patient groups was estimated by the Kaplan-Meier method and 2-sided log-rank test in GraphPad Prism Version 6.01."}], "state": "complete"}, {"id": "claim-data-access", "statement": "A cohort of 164 glioma specimens from the Chinese Glioma Genome Atlas (CGGA) array database were assessed as the training group. Samples were obtained from the Chinese Glioma Genome Atlas (CGGA) dataset (the training set);the TCGA RNA-seq database and GSE16011 array dataset were assessed as independent validation sets. 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Moreover, HOXA7-siRNA inhibited migration and invasion in vitro, a", "ified in the long OS group. Cell culture and transfection of HOXA7-siRNA Human glioma U251 cells were", "hased from Genepharma (Shanghai, China), and transfected into U251 cells using Lipofectamine™ 2000 (I", "roup. Cell culture and transfection of HOXA7-siRNA Human glioma U251 cells were obtained from t"], "order_basis": "paper_text_order:738", "id": "assay:1"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.85, "evidence": ["able 2; there were more patients (n=12) with Ki67 overexpression in the high-risk group compar"], "order_basis": "paper_text_order:2010", "id": "assay:2"}, {"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["d with HOXA7-siRNA for 48h before RT-PCR and Western blot assays [27]. SUPPLEMENTARY MATERIALS FIGURE"], "order_basis": "paper_text_order:5904", "id": "assay:3"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["logrank_test"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["OS in high- and low-risk patient groups was estimated by the Kaplan-Meier method and 2-sided log-rank test in GraphPad Prism Version 6.01."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}