Evidence map›Paper›PMID 32762026›Full record

ArticleJournal of cellular and molecular medicine2020

The identification of six risk genes for ovarian cancer platinum response based on global network algorithm and verification analysis.

Linan Xing, Wanqi Mi, Yongjian Zhang, Songyu Tian, Yunyang Zhang, Rui Qi, Ge Lou, Chunlong Zhang

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Review
  2. Biomedicines · 2021
    Article
  3. Review
  4. Article
  5. What is new about ovarian malignancies?Contemporary oncology (Poznan, Poland) · 2021
    Review
  6. Article
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

8 authors.

Linan XingDepartment of Gynecology, Harbin Medical University Cancer Hospital, Harbin, China.ORCID 0000-0001-7325-6726
Wanqi MiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.ORCID 0000-0002-5263-1635
Yongjian ZhangDepartment of Gynecology, Harbin Medical University Cancer Hospital, Harbin, China.
Songyu TianDepartment of Gynecology, Harbin Medical University Cancer Hospital, Harbin, China.
Yunyang ZhangDepartment of Gynecology, Harbin Medical University Cancer Hospital, Harbin, China.
Rui QiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Ge LouDepartment of Gynecology, Harbin Medical University Cancer Hospital, Harbin, China.
Chunlong ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer is the most lethal gynaecological cancer, and resistance of platinum-based chemotherapy is the main reason for treatment failure. The aim of the present study was to identify candidate genes involved in ovarian cancer platinum response by analysing genes from homologous recombination and Fanconi anaemia pathways. Associations between these two functional genes were explored in the study, and we performed a random walk algorithm based on reconstructed gene-gene network, including protein-protein interaction and co-expression relations. Following the random walk, all genes were ranked and GSEA analysis showed that the biological functions focused primarily on autophagy, histone modification and gluconeogenesis. Based on three types of seed nodes, the top two genes were utilized as examples. We selected a total of six candidate genes (FANCA, FANCG, POLD1, KDM1A, BLM and BRCA1) for subsequent verification. The validation results of the six candidate genes have significance in three independent ovarian cancer data sets with platinum-resistant and platinum-sensitive information. To explore the correlation between biomarkers and clinical prognostic factors, we performed differential analysis and multivariate clinical subgroup analysis for six candidate genes at both mRNA and protein levels. And each of the six candidate genes and their neighbouring genes with a mutation rate greater than 10% were also analysed by network construction and functional enrichment analysis. In the meanwhile, the survival analysis for platinum-treated patients was performed in the current study. Finally, the RT-qPCR assay was used to determine the performance of candidate genes in ovarian cancer platinum response. Taken together, this research demonstrated that comprehensive bioinformatics methods could help to understand the molecular mechanism of platinum response and provide new strategies for overcoming platinum resistance in ovarian cancer treatment.

Indexed as

AdultAgedAged, 80 and overAlgorithmsCell Line, TumorDisease-Free SurvivalDNA Polymerase IIIDrug Resistance, NeoplasmFanconi AnemiaFanconi Anemia Complementation Group A ProteinFanconi Anemia Complementation Group G ProteinFemaleGene Expression Regulation, NeoplasticHistone DemethylasesHomologous RecombinationHumansBloom syndrome proteinDNA Polymerase IIIFANCA protein, humanFANCG protein, humanFanconi Anemia Complementation Group A ProteinFanconi Anemia Complementation Group G ProteinHistone DemethylasesKDM1A protein, humanPlatinumPOLD1 protein, humanRecQ HelicasesFanconi anaemiahomologous recombinationovarian cancerplatinum treatment

Identifiers

PMID32762026
PMCPMC7520306

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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.