Evidence map›Paper›PMID 33045680›Full record

ArticleTranslational oncology2021

Protein anabolism is key to long-term survival in high-grade serous ovarian cancer.

Lingxiang Wang, Tao Sun, Shumei Li, Zhengmao Zhang, Jingde Jia, Baoen Shan

Open access · goldAbstract read
In one paragraph

Article in Translational oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 40% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Identifying Explainable Machine Learning Models and a Novel SFRP2International journal of molecular sciences · 2023
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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

6 authors at 2 institutions in 1 country.

Lingxiang WangDepartment of Gynecology, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, 12 Jiankang Road, Shijiazhuang, Hebei 050011, China; Cancer Institute, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, 12 Jiankang Road, Shijiazhuang, Hebei 050011, China.
Tao SunDepartment of Orthopaedic Surgery, Hebei Medical University Third Affiliated Hospital, 139 Ziqiang Road, Shijiazhuang, Hebei 050051, China.
Shumei LiCancer Institute, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, 12 Jiankang Road, Shijiazhuang, Hebei 050011, China.
Zhengmao ZhangDepartment of Gynecology, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, 12 Jiankang Road, Shijiazhuang, Hebei 050011, China.
Jingde JiaDepartment of Gynecology, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, 12 Jiankang Road, Shijiazhuang, Hebei 050011, China.
Baoen ShanCancer Institute, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, 12 Jiankang Road, Shijiazhuang, Hebei 050011, China. Electronic address: baoenshan@hotmail.com.
Hebei Medical University · CNFourth Hospital of Hebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to identify the biological processes associated with long-term survival in high-grade serous ovarian cancer (HGSOC). HGSOC cases obtained from The Cancer Genome Atlas Ovarian Cancer (TCGA-OV) database were divided into long-term survivors (LTS) and normal-term survivors (NTS) based on survival cutoffs defined by the HGSOC cohort in the SEER database. Differentially expressed genes (DEGs) were screened using the generalized linear modeling (GLM) method. Gene Ontology (GO) functional and KEGG pathway enrichment analyses were performed using DAVID Bioinformatics Resources. DEG-related protein-protein interactions (PPI) were extracted from the STRING database and hub genes were identified using CytoHubba in the Cytoscape program. In total, 157 DEGs, including 155 upregulated and 2 downregulated genes, were identified. Upregulated genes were statistically enriched in 80 GO terms and 11 KEGG pathways related to energy and substrate metabolism, such as protein absorption, digestion, and metabolism as well as signaling pathways, including chromatin silencing, regulation of ERK1 and ERK2 cascade, and regulation of MAPKKK. ALB and POMC were the common hub genes. These findings reveal that protein anabolism is crucial to long-term survival, regulated by activation of the MAPK/ERK signaling pathway and chromatin silencing. Comprehensive understanding of the molecular mechanisms via further exploration may contribute toward an effective treatment for ovarian cancer.

Indexed as

Gene expression profilingLong-term survivorOvarian cancerProtein anabolism

Identifiers

PMID33045680
PMCPMC7557892
OpenAlexW3092483151

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.