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pmid:33682883

An autophagy-related prognostic signature associated with immune microenvironment features of uveal melanoma.

Zhuotao Zheng · Lingyue Zhang · Zewei Tu · Yan Deng · Xiaolong Yin

Bioscience reports · 2021 doi:10.1042/BSR20203812

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

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:33682883
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science-record
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2026-11-01T15:41:27Z
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2026-11-01T22:03:16Z
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paper object · 10 fields
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title
An autophagy-related prognostic signature associated with immune microenvironment features of uveal melanoma.
doi
10.1042/BSR20203812
pmid
33682883
authors array · 5 items
[0]
Zhuotao Zheng
[1]
Lingyue Zhang
[2]
Zewei Tu
[3]
Yan Deng
[4]
Xiaolong Yin
journal
Bioscience reports
year
2021
abstract
Autophagy is involved in cancer initiation and progression but its role in uveal melanoma (UM) was rarely investigated. Herein, we built an autophagy-related gene (ARG) risk model of UM patients by univariate Cox regression and least absolute shrinkage and selection operator (Lasso) regression model and filtrated out nine prognostic ARGs in The Cancer Genome Atlas (TCGA) cohort. Survival and Receiver Operating Characteristic (ROC) Curve analysis in the TCGA and other four independent UM cohorts (GSE22138, GSE27831, GSE44295 and GSE84976) proved that the ARG-signature possessed robust and steady prognosis predictive ability. We calculated risk scores for patients included in our study and patients with higher risk scores showed worse clinical outcomes. We found the expressions of the nine ARGs were significantly associated with clinical and molecular features (including risk score) and overall survival (OS) of UM patients. Furthermore, we utilized univariate and multivariate Cox regression analyses to determine the independent prognostic ability of the ARG-signature. Functional enrichment analysis showed the ARG-signature was correlated with several immune-related processes and pathways like T-cell activation and T-cell receptor signaling pathway. Gene set enrichment analysis (GSEA) found tumor hallmarks including angiogenesis, IL6-JAK-STAT3-signaling, reactive oxygen species pathway and oxidative phosphorylation were enriched in high-risk UM patients. Finally, infiltrations of several immune cells and immune-related scores were found significantly associated with the ARG-signature. In conclusion, the ARG-signature might be a strong predictor for evaluating the prognosis and immune infiltration of UM patients.
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Based on the clinical and survival information, univariate and multivariate Cox regression were the vital analytical methods to decide the independent prognostic role of the ARG-signature.
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Based on the clinical and survival information, univariate and multivariate Cox regression were the vital analytical methods to decide the independent prognostic role of the ARG-signature.
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sections[18] "Data Availability" paragraph 2
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The data analyzed in the present study can be accessed the TCGA (http://cancergenome.nih.gov/) and GEO (https://www.ncbi.nlm.nih.gov/geo/) websites.
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Syntenin-1 is expressed in uveal melanoma and correlates with metastatic progression
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Baseline information of UM patients included in the study
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Thickness (mm)
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[5]
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[31] array · 7 items
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[1]
≤10
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37 (46.25%)
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10 (15.87%)
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[1]
>10
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43 (53.75%)
[3]
53 (84.13%)
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[6]
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[33] array · 7 items
[0]
[1]
NA
[2]
0 (0.00%)
[3]
0 (0.00%)
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[34] array · 7 items
[0]
Chr 6p gain
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[2]
[3]
[4]
[5]
[6]
[35] array · 7 items
[0]
[1]
Yes
[2]
23 (28.75%)
[3]
/
[4]
/
[5]
/
[6]
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[36] array · 7 items
[0]
[1]
No
[2]
57 (71.25%)
[3]
/
[4]
/
[5]
/
[6]
/
[37] array · 7 items
[0]
[1]
NA
[2]
0 (0)
[3]
/
[4]
/
[5]
/
[6]
/
[38] array · 7 items
[0]
Chr 8q gain
[1]
[2]
[3]
[4]
[5]
[6]
[39] array · 7 items
[0]
[1]
Yes
[2]
32 (40.00%)
[3]
/
[4]
/
[5]
/
[6]
/
[40] array · 7 items
[0]
[1]
No
[2]
48 (60.00%)
[3]
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[4]
/
[5]
/
[6]
/
[41] array · 7 items
[0]
[1]
NA
[2]
0 (0)
[3]
/
[4]
/
[5]
/
[6]
/
[42] array · 7 items
[0]
Chr1 loss
[1]
[2]
[3]
[4]
[5]
[6]
[43] array · 7 items
[0]
[1]
Yes
[2]
9 (11.25%)
[3]
/
[4]
/
[5]
/
[6]
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[44] array · 7 items
[0]
[1]
No
[2]
71 (88.75%)
[3]
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[4]
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[5]
/
[6]
/
[45] array · 7 items
[0]
[1]
NA
[2]
0 (0)
[3]
/
[4]
/
[5]
/
[6]
/
[46] array · 7 items
[0]
Chr3 loss
[1]
[2]
[3]
[4]
[5]
[6]
[47] array · 7 items
[0]
[1]
Yes
[2]
31 (38.75%)
[3]
37 (58.73%)
[4]
/
[5]
14 (50.00%)
[6]
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[48] array · 7 items
[0]
[1]
No
[2]
49 (61.25%)
[3]
18 (28.57%)
[4]
/
[5]
14 (50.00%)
[6]
/
[49] array · 7 items
[0]
[1]
NA
[2]
0 (0)
[3]
8 (12.70%)
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[5]
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[6]
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locator
section[3]/table-wrap[1]#T1
[6] object · 16 fields
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asset:table:pmid:33682883:2
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jats-table
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application/vnd.jats.table+json
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read_table
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section[10]/table-wrap[1]#T2
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null
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Univariate Cox regression analysis of the nine ARGs in the TCGA cohort
structure object · 5 fields
pmcid
PMC7982771
section_index
10
section_title
Development of the ARG-signature in UM patients
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10
column_count
6
table object · 8 fields
label
Table 2
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Univariate Cox regression analysis of the nine ARGs in the TCGA cohort
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[0]
ARGs
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HR
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HR.95L
[3]
HR.95H
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Coefficient
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[0]
TUSC1
[1]
2.1716
[2]
1.5322
[3]
3.0778
[4]
<0.0001
[5]
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[0]
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[1]
0.6813
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0.5515
[3]
0.8418
[4]
0.0004
[5]
−0.0480
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[0]
GABARAPL1
[1]
1.0242
[2]
1.0125
[3]
1.0361
[4]
<0.0001
[5]
−0.0411
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[0]
PRKCD
[1]
0.8149
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0.7370
[3]
0.9010
[4]
0.0001
[5]
−0.0319
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[0]
DLC1
[1]
1.6332
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1.3017
[3]
2.0491
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<0.0001
[5]
−0.0146
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[0]
FKBP1A
[1]
1.9597
[2]
1.4198
[3]
2.7050
[4]
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0.0035
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ITGA6
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0.1594
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0.0571
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0.4447
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0.0930
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BNIP1
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0.8626
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0.7972
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0.9333
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0.0002
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IKBKE
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0.6954
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0.5867
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0.8243
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0.1870
locator
section[10]/table-wrap[1]#T2
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[0]
asset:data:geo:GSE22138 not downloaded
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[3]
asset:data:geo:GSE27831 licence not read
[4]
asset:data:geo:GSE44295 not downloaded
[5]
asset:data:geo:GSE44295 licence not read
[6]
asset:data:geo:GSE84976 not downloaded
[7]
asset:data:geo:GSE84976 licence not read
analysis object · 4 fields
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complete
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[0] object · 10 fields
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method-1
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survival_analysis
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cox_ph
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time_to_event_with_censoring
evidence object · 3 fields
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quote
Based on the clinical and survival information, univariate and multivariate Cox regression were the vital analytical methods to decide the independent prognostic role of the ARG-signature.
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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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correlation_analysis
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pearson_r
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paired_numeric_columns
evidence object · 3 fields
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0.8
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method-4
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diagnostic_evaluation
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roc
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Diagnostic test evaluation
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confusion_counts
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roc_curve
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sensitivity_specificity
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solve_confusion_matrix
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classification_metrics
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published_precision_envelope
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parameters object · 0 fields
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reference_standard_and_test
evidence object · 3 fields
score
0.8
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high
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ROC analysis
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gaps array · 0 items
capability object · 3 fields
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complete
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capability_id
capability:computational_analysis
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meta_analysis
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gwas
candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
state
complete
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nothing:replicable_now
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method object · 5 fields
tier
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required_operations array · 1 item
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cox_ph
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 4 items
[0]
GSE22138
[1]
GSE27831
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GSE44295
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GSE84976
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[0]
GSE22138
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GSE27831
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GSE44295
[3]
GSE84976
statements array · 1 item
[0]
The data analyzed in the present study can be accessed the TCGA (http://cancergenome.nih.gov/) and GEO (https://www.ncbi.nlm.nih.gov/geo/) websites.
basis
The paper names GSE22138, GSE27831, GSE44295, GSE84976 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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cox_ph
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source:pmid:33682883
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asset:table:pmid:33682883:2
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run_analysis
must_build object · 5 fields
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data:geo:GSE22138
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partial
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extraction_review
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MiniMax-M3.1-Flash
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minimax
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minimax
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single_reader
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verbatim
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verbatim
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source:pmid:33682883
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data:geo:GSE22138
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GEO GSE22138
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pmid:33682883
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source:pmid:33682883
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PMID 33682883 full text
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data:geo:GSE22138
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GEO GSE22138
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agent:corpus-assay-engine
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agent:minimax-reader
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red in published researches [16,17]. For the microarray data in the GSE22138, GSE27831, GSE44295 and
[1]
quantile normalization were performed on the microarray raw data using a robust multiarray averaging
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Based on the clinical and survival information, univariate and multivariate Cox regression were the vital analytical methods to decide the independent prognostic role of the ARG-signature.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33682883", "kind": "science-record", "revision": 7, "content_hash": "sha256:3ef45c9a270811dfe3bcd0a14e87bd8ba2eb02befe414a5de0caa93722180a37", "created_at": "2026-11-01T15:41:27Z", "updated_at": "2026-11-01T22:03:16Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "An autophagy-related prognostic signature associated with immune microenvironment features of uveal melanoma.", "doi": "10.1042/BSR20203812", "pmid": "33682883", "authors": ["Zhuotao Zheng", "Lingyue Zhang", "Zewei Tu", "Yan Deng", "Xiaolong Yin"], "journal": "Bioscience reports", "year": 2021, "abstract": "Autophagy is involved in cancer initiation and progression but its role in uveal melanoma (UM) was rarely investigated. Herein, we built an autophagy-related gene (ARG) risk model of UM patients by univariate Cox regression and least absolute shrinkage and selection operator (Lasso) regression model and filtrated out nine prognostic ARGs in The Cancer Genome Atlas (TCGA) cohort. Survival and Receiver Operating Characteristic (ROC) Curve analysis in the TCGA and other four independent UM cohorts (GSE22138, GSE27831, GSE44295 and GSE84976) proved that the ARG-signature possessed robust and steady prognosis predictive ability. We calculated risk scores for patients included in our study and patients with higher risk scores showed worse clinical outcomes. We found the expressions of the nine ARGs were significantly associated with clinical and molecular features (including risk score) and overall survival (OS) of UM patients. Furthermore, we utilized univariate and multivariate Cox regression analyses to determine the independent prognostic ability of the ARG-signature. Functional enrichment analysis showed the ARG-signature was correlated with several immune-related processes and pathways like T-cell activation and T-cell receptor signaling pathway. Gene set enrichment analysis (GSEA) found tumor hallmarks including angiogenesis, IL6-JAK-STAT3-signaling, reactive oxygen species pathway and oxidative phosphorylation were enriched in high-risk UM patients. Finally, infiltrations of several immune cells and immune-related scores were found significantly associated with the ARG-signature. 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