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pmid:36871208

Prognostic implication of cuproptosis related genes associates with immunity in Ewing's sarcoma.

Qingbo Li · Xiao Xu · Xiejia Jiao

Translational oncology · 2023 doi:10.1016/j.tranon.2023.101646

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:36871208
kind
science-record
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sha256:9a933c376c2f26b47e3f6aac46f4dae1b0ad544c8dd52dd0e49349c6cc978e22
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https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T19:01:30Z
updated_at
2026-11-01T21:30:17Z
generator object · 2 fields
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paper object · 10 fields
state
complete
title
Prognostic implication of cuproptosis related genes associates with immunity in Ewing's sarcoma.
doi
10.1016/j.tranon.2023.101646
pmid
36871208
authors array · 3 items
[0]
Qingbo Li
[1]
Xiao Xu
[2]
Xiejia Jiao
journal
Translational oncology
year
2023
abstract
Growing evidence demonstrated that cuproptosis play critical roles in human cancers. We aimed to identify the roles of cuproptosis related genes (CRGs) in prognosis and immunity of Ewing's sarcoma. The data of GSE17674 and GSE63156 were obtained from GEO. The expression of 17 CRGs and immune cells were explored, then correlation was analyzed. Based on CRGs, two molecular clusters were identified by consensus clustering algorithm. KM survival and IME features including immune cells, immune response, checkpoint genes between clusters were evaluated. NFE2L2, LIAS, and CDKN2A were screened out as prognostic signatures by univariate, LASSO and step regression. A risk model was established, and validated by KM method with p = 0.0026, and perfect AUC values. The accuracy of risk model was also well validated in external dataset. A nomogram was constructed and evaluated by calibration curves and DCA. Low level of immune cells, immune response, and enriched checkpoint genes were found in high-risk group. GSEA of signatures and GSVA of ES-related pathways revealed the potential molecular mechanism involved in ES progression. Several drugs showed sensitivity to ES samples. DEGs between risk groups were screened out, and function enrichment was conducted. Finally, scRNA analysis of GSE146221 was done. NFE2L2, and LIAS played crucial role in the evolution of ES by pesudotime and trajectory methods. Our study provided new aspects for further research in ES.
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Univariate Cox regression (p < 0.06) was applied to generate the prognostic CRGs. Then LASSO algorithm with lambda.min was used to reduce variables [20]. Finally, CRGs signatures were screened out by multivariate step regression with the lowest Akaike information criterion (AIC) via "survival" package [21].
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sections[6] "Survival analysis and risk model construction" paragraph 2
quote
Univariate Cox regression (p < 0.06) was applied to generate the prognostic CRGs. Then LASSO algorithm with lambda.min was used to reduce variables [20]. Finally, CRGs signatures were screened out by multivariate step regression with the lowest Akaike information criterion (AIC) via "survival" package [21].
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The data used in this study are available in publicly in GEO.
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sections[29] "Data availability" paragraph 2
quote
The data used in this study are available in publicly in GEO.
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A risk model was established, and validated by KM method with p = 0.0026, and perfect AUC values.
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0.0026
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A risk model was established, and validated by KM method with p = 0.0026, and perfect AUC values.
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sections[0] "Abstract" paragraph 4
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A risk model was established, and validated by KM method with p = 0.0026, and perfect AUC values.
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A risk model was established, and validated by KM method with p = 0.0026, and perfect AUC values.
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https://doi.org/10.1016/j.tranon.2023.101646
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10.1016/j.tranon.2023.101646
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The data used in this study are available in publicly in GEO.
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The data used in this study are available in publicly in GEO.
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Homo sapiens
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Single cell transcriptomics of Ewing Sarcoma cell lines
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null
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570
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Homo sapiens
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Inflammatory gene profiling of Ewing sarcoma family of tumors (set B)
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GSM1542416
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GSM1542417
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39
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null
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null
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5175
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Homo sapiens
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Gene Expression Profiling of Ewing Sarcoma Tumors Reveals the Prognostic Importance of Tumor-Stromal Interactions [EuroEwing]
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null
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null
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The data used in this study are available in publicly in GEO.
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The data used in this study are available in publicly in GEO.
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74
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null
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5175
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Homo sapiens
title
Exon array profiles of primary human Ewing sarcoma tumors
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Univariate Cox regression (p < 0.06) was applied to generate the prognostic CRGs. Then LASSO algorithm with lambda.min was used to reduce variables [20]. Finally, CRGs signatures were screened out by multivariate step regression with the lowest Akaike information criterion (AIC) via "survival" package [21].
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[1]
asset:data:geo:GSE146221 not downloaded
[2]
asset:data:geo:GSE17674 licence not read
[3]
asset:data:geo:GSE17674 not downloaded
[4]
asset:data:geo:GSE63156 licence not read
[5]
asset:data:geo:GSE63156 not downloaded
[6]
asset:data:geo:GSE68776 licence not read
[7]
asset:data:geo:GSE68776 not downloaded
[8]
execution.not_run
[9]
review.human_critique
[10]
review.independent_reader
[11]
review.machine_critique
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f2132e96ae6c7a4e
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source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
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Univariate Cox regression (p < 0.06) was applied to generate the prognostic CRGs. Then LASSO algorithm with lambda.min was used to reduce variables [20]. Finally, CRGs signatures were screened out by multivariate step regression with the lowest Akaike information criterion (AIC) via "survival" package [21].
order_basis
analysis_only
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Complete file
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The expression of 17 CRGs and immune cells were explored, then correlation was analyzed. Based on CRGs, two molecular clusters were identified by consensus clustering algorithm. KM survival and IME features including immune cells, immune response, checkpoint genes between clusters were evaluated. NFE2L2, LIAS, and CDKN2A were screened out as prognostic signatures by univariate, LASSO and step regression. A risk model was established, and validated by KM method with p = 0.0026, and perfect AUC values. The accuracy of risk model was also well validated in external dataset. A nomogram was constructed and evaluated by calibration curves and DCA. Low level of immune cells, immune response, and enriched checkpoint genes were found in high-risk group. GSEA of signatures and GSVA of ES-related pathways revealed the potential molecular mechanism involved in ES progression. Several drugs showed sensitivity to ES samples. 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