Evidence map›Paper›PMID 35227285›Full record

ArticleJournal of ovarian research2022

Construction and validation of a transcription factors-based prognostic signature for ovarian cancer.

Qingyuan Cheng, Liman Li, Mingxia Yu

Open access · goldAbstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of ovarian research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.8field-weighted citation impact, top 8% 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

9 citing papers in PubMed, 26 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Qingyuan Cheng *Department of Andrology/Sichuan Human Sperm Bank, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, P. R. China.
Liman Li *Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China.
Mingxia YuDepartment of Clinical Laboratory, Zhongnan Hospital of Wuhan University, Wuhan, China. dewrosy520@whu.edu.cn.
Sichuan University · CNWuhan University · CN

Funding

health commission of hubei province scientific research project WJ2019M203national natural science foundation of china 81472033
6 · The paper itself

Abstract

backgroundOvarian cancer (OC) is one of the most common and lethal malignant tumors worldwide and the prognosis of OC remains unsatisfactory. Transcription factors (TFs) are demonstrated to be associated with the clinical outcome of many types of cancers, yet their roles in the prognostic prediction and gene regulatory network in patients with OC need to be further investigated.

methodsTFs from GEO datasets were collected and analyzed. Differential expression analysis, WGCNA and Cox-LASSO regression model were used to identify the hub-TFs and a prognostic signature based on these TFs was constructed and validated. Moreover, tumor-infiltrating immune cells were analyzed, and a nomogram containing age, histology, FIGO_stage and TFs-based signature were established. Potential biological functions, pathways and the gene regulatory network of TFs in signature was also explored.

resultsIn this study, 6 TFs significantly associated with the prognosis of OC were identified. These TFs were used to build up a TFs-based signature for predicting the survival of patients with OC. Patients with OC in training and testing datasets were divided into high-risk and low-risk groups, according to the median value of risk scores determined by the signature. The two groups were further used to validate the performance of the signature, and the results showed the TFs-based signature had effective prediction ability. Immune infiltrating analysis was conducted and abundance of B cells naïve, T cells CD4 memory resting, Macrophages M2 and Mast cells activated were significantly higher in high-risk group. A nomogram based on the signature was established and illustrated good predictive efficiencies for 1, 2, and 3-year overall survival. Furthermore, the construction of the TFs-target gene regulatory network revealed the potential mechanisms of TFs in OC.

conclusionsTo our best knowledge, it is for the first time to develop a prognostic signature based on TFs in OC. The TFs-based signature is proven to be effective in predicting the survival of patients with OC. Our study may facilitate the clinical decision-making for patients with OC and help to elucidate the underlying mechanism of TFs in OC.

Indexed as

NomogramsOvarian NeoplasmsTranscription FactorsAge FactorsBasic Helix-Loop-Helix Leucine Zipper Transcription FactorsB-LymphocytesCD4-Positive T-LymphocytesDatabases, GeneticDNA-Binding ProteinsFemaleHeat Shock Transcription FactorsHumansImmunological Memory CellsLymphocytes, Tumor-InfiltratingMacrophagesMast CellsBasic Helix-Loop-Helix Leucine Zipper Transcription FactorsDNA-Binding ProteinsHeat Shock Transcription FactorsHSF1 protein, humanMLXIP protein, humanRFXANK protein, humanSNAI2 protein, humanSnail Family Transcription FactorsTranscription FactorsZNF304 protein, humanZNF518A protein, humannomogramovarian cancerprognosissignaturetranscription factor

Identifiers

PMID35227285
PMCPMC8886838
OpenAlexW4214528226

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.