Evidence map›Paper›PMID 37337170›Full record

ArticleBMC medical genomics2023

A novel extrachromosomal circular DNA related genes signature for overall survival prediction in patients with ovarian cancer.

Ying Zhang, Kexian Dong, Xueyuan Jia, Shuomeng Du, Dong Wang, Liqiang Wang, Han Qu, Shihao Zhu, Yang Wang, Zhao Wang and 3 more

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.1field-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

13 citing papers in PubMed, 13 citations in OpenAlex.

  1. Functional role of small extrachromosomal circular DNA in colorectal cancer.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Role of solute carrier transporters in ovarian cancer (Review).International journal of molecular medicine · 2025
    Review
  8. Review
  9. ECGA: A web server to explore and analyze extrachromosomal gene in cancer.Computational and structural biotechnology journal · 2024
    Article
  10. Article
  11. Article
  12. Human sulfotransferaseFrontiers in genetics · 2024
    Review
  13. 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

13 authors at 1 institution in 1 country.

Ying Zhang *Laboratory of Medical Genetics, Harbin Medical University, Harbin, 150081, China.
Kexian Dong *Laboratory of Medical Genetics, Harbin Medical University, Harbin, 150081, China.
Xueyuan Jia *Laboratory of Medical Genetics, Harbin Medical University, Harbin, 150081, China.
Shuomeng DuLaboratory of Medical Genetics, Harbin Medical University, Harbin, 150081, China.
Dong WangScientific Research Centre, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150081, China.
Liqiang WangLaboratory of Medical Genetics, Harbin Medical University, Harbin, 150081, China.
Han QuLaboratory of Medical Genetics, Harbin Medical University, Harbin, 150081, China.
Shihao ZhuLaboratory of Medical Genetics, Harbin Medical University, Harbin, 150081, China.
Yang WangLaboratory of Medical Genetics, Harbin Medical University, Harbin, 150081, China.
Zhao WangDepartment of Gynecology, Harbin Medical University Cancer Hospital, Harbin, 150081, China.
Shuopeng ZhangLaboratory of Medical Genetics, Harbin Medical University, Harbin, 150081, China.
Wenjing SunLaboratory of Medical Genetics, Harbin Medical University, Harbin, 150081, China.
Songbin FuLaboratory of Medical Genetics, Harbin Medical University, Harbin, 150081, China. fusb@ems.hrbmu.edu.cn.
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveOvarian cancer (OV) has a high mortality rate all over the world, and extrachromosomal circular DNA (eccDNA) plays a key role in carcinogenesis. We wish to study more about the molecular structure of eccDNA in the UACC-1598-4 cell line and how its genes are associated with ovarian cancer prognosis.

methodsWe sequenced and annotated the eccDNA by Circle_seq of the OV cell line UACC-1598-4. To acquire the amplified genes of OV on eccDNA, the annotated eccDNA genes were intersected with the overexpression genes of OV in TCGA. Univariate Cox regression was used to find the genes on eccDNA that were linked to OV prognosis. The least absolute shrinkage and selection operator (LASSO) and cox regression models were used to create the OV prognostic model, as well as the receiver operating characteristic curve (ROC) curve and nomogram of the prediction model. By applying the median value of the risk score, the samples were separated into high-risk and low-risk groups, and the differences in immune infiltration between the two groups were examined using ssGSEA.

resultsEccDNA in UACC-1598-4 has a length of 0-2000 bp, and some of them include the whole genes or gene fragments. These eccDNA originated from various parts of chromosomes, especially enriched in repeatmasker, introns, and coding regions. They were annotated with 2188 genes by Circle_seq. Notably, the TCGA database revealed that a total of 198 of these eccDNA genes were overexpressed in OV (p < 0.05). They were mostly enriched in pathways associated with cell adhesion, ECM receptors, and actin cytoskeleton. Univariate Cox analysis showed 13 genes associated with OV prognosis. LASSO and Cox regression analysis were used to create a risk model based on remained 9 genes. In both the training (TCGA database) and validation (International Cancer Genome Consortium, ICGC) cohorts, a 9-gene signature could successfully discriminate high-risk individuals (all p < 0.01). Immune infiltration differed significantly between the high-risk and low-risk groups. The model's area under the ROC curve was 0.67, and a nomograph was created to assist clinician.

conclusionEccDNA is found in UACC-1598-4, and part of its genes linked to OV prognosis. Patients with OV may be efficiently evaluated using a prognostic model based on eccDNA genes, including SLC7A1, NTN1, ADORA1, PADI2, SULT2B1, LINC00665, CILP2, EFNA5, TOMM.

Indexed as

DNAOvarian NeoplasmsCarcinogenesisDNA, CircularFemaleHumansIntronsPrognosisDNADNA, CirculareccDNAImmune infiltrationOvarian cancerPrognostic modelTCGA

Identifiers

PMID37337170
PMCPMC10278296
OpenAlexW4381164946

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.