Evidence map›Paper›PMID 35958490›Full record

ArticleAmerican journal of translational research2022

Constructing a novel prognostic signature of tumor driver genes for breast cancer.

Liqiang Zhou, Yali Yi, Chuan Liu, Zhiqing Chen

Open access · greenAbstract read
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Article in American journal of translational research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Liqiang ZhouDepartment of General Surgery, The Second Affiliated Hospital of Nanchang University Nanchang 330006, Jiangxi, China.
Yali YiDepartment of Oncology, The Second Affiliated Hospital of Nanchang University Nanchang 330006, Jiangxi, China.
Chuan LiuKey Laboratory of Molecular Medicine of Jiangxi Province, The Second Affiliated Hospital of Nanchang University Nanchang 330006, Jiangxi, China.
Zhiqing ChenKey Laboratory of Molecular Medicine of Jiangxi Province, The Second Affiliated Hospital of Nanchang University Nanchang 330006, Jiangxi, China.
Nanchang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo systematically explore the function and prognostic ability of tumor-driver genes (TDGs) in breast carcinoma (BRCA).

methodsFunctional enrichment analysis of BRCA differentially expressed TDGs was assesed. We used univariate Cox, lasso, and multivariate Cox regression to identify the independent prognostic TDGs of BRCA. Then we constructed a prognostic signature and verified its predictive performance. Gene set enrichment analysis of the signal pathway revealed the differences between the prognostic signature high- and low-risk groups. Finally, a nomogram related to the prognostic model was established and verified.

resultsA total of 595 differentially expressed TDGs were identified, which are related to various molecular mechanisms of BRCA progression. We identified 8 independent prognostic TDGs for BRCA and validated their expression and prognosis with public data and clinical samples. The BRCA cohort was divided into training and validation cohorts, and prognostic signatures were constructed separately. The log-rank test showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group in the prognostic signature (P<0.001); the AUC in the three cohorts were 0.805, 0.712, and 0.760, respectively; the nomogram also showed better predictive performance. Analyzing the difference between the two risk subtypes, the high-risk group is mainly enriched in angiogenesis, MTORC1, epithelial-mesenchymal transition and glycolysis, which means it is highly malignant.

conclusionsThe prognostic signature and nomogram was confirmed to accurately predict the prognosis of patients with BRCA and we validated the hub genes, suggesting their potential as future therapeutic targets.

Indexed as

Breast cancernomogramprognostic signaturetumor drive gene

Identifiers

PMID35958490
PMCPMC9360863
OpenAlexW4291676441

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.