Evidence map›Paper›PMID 32582991›Full record

ArticleOncology reports2020

Identification of a prognosis‑associated signature associated with energy metabolism in triple‑negative breast cancer.

Chao Li, Xujun Li, Guangming Li, Long Sun, Wei Zhang, Jing Jiang, Qidong Ge

Open access · hybridAbstract read
In one paragraph

Article in Oncology reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 18 citations in OpenAlex.

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  13. Glucose Metabolism in Cancer: The Warburg Effect and Beyond.Advances in experimental medicine and biology · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Chao LiDepartment of Breast Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, Zhejiang 315000, P.R. China.
Xujun LiDepartment of Breast Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, Zhejiang 315000, P.R. China.
Guangming LiDepartment of Breast Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, Zhejiang 315000, P.R. China.
Long SunDepartment of Breast Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, Zhejiang 315000, P.R. China.
Wei ZhangDepartment of Breast Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, Zhejiang 315000, P.R. China.
Jing JiangDepartment of Breast Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, Zhejiang 315000, P.R. China.
Qidong GeDepartment of Breast Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, Zhejiang 315000, P.R. China.
University of Chinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

At present, a large number of exciting results have been found regarding energy metabolism within the triple‑negative breast cancer (TNBC) field. Apart from aerobic glycolysis, a number of other catabolic pathways have also been demonstrated to participate in energy generation. However, the prognostic value of energy metabolism for TNBC currently remains unclear. In the present study, the association between gene expression profiles of energy metabolism and outcomes in patients with TNBC was examined using datasets obtained from the Gene Expression Omnibus and The Cancer Genome Atlas. In total, four robust TNBC subtypes were identified on the basis of negative matrix factorization clustering and gene expression patterns, which exhibited distinct immunological, molecular and prognostic (disease‑free survival) features. The differentially expressed genes were subsequently identified from the subgroup that demonstrated the poorest prognosis compared with the remaining 3 subgroups, where their biological functions were assessed further by means of gene ontology enrichment analysis. Any signatures found to be associated with energy metabolism were then established using the Cox proportional hazards model to assess patient prognosis. According to results of Kaplan‑Meier analysis, the constructed signature consisting of eight genes that were associated with energy metabolism distinguished patient outcomes into low‑ and high‑risk groups. In addition, this signature, which was found to be markedly associated with the clinical characteristics of the patients, served as an independent factor in predicting TNBC patient prognosis. According to gene set enrichment analysis, the gene sets related to the high‑risk group participated in the MAPK signal transduction pathway, focal adhesion and extracellular matrix receptor interaction, whilst those related to the low‑risk group were revealed to be mainly associated with mismatch repair and propanoate metabolism. Findings from the present study shed new light on the role of energy metabolism within TNBC, where the eight‑gene signature associated with energy metabolism constructed can be utilized as a new prognostic marker for predicting survival in patients with TNBC.

Indexed as

Energy MetabolismFemaleHumansMiddle AgedPrognosisTranscriptomeTriple Negative Breast Neoplasmsenergy metabolismtriple-negative breast cancer

Identifiers

PMID32582991
PMCPMC7388543
OpenAlexW3036645975

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.