Evidence map›Paper›PMID 32950050›Full record

ArticleJournal of ovarian research2020

A novel signature of two long non-coding RNAs in BRCA mutant ovarian cancer to predict prognosis and efficiency of chemotherapy.

Yinglian Pan, Li Ping Jia, Yuzhu Liu, Yiyu Han, Qian Li, Qin Zou, Zhongpei Zhang, Jin Huang, Qingchun Deng

Open access · goldAbstract read
In one paragraph

Article in Journal of ovarian research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 49% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

9 authors at 2 institutions in 1 country.

Yinglian PanDepartment of Medical Oncology, The First Affiliated Hospital of Hainan Medical University, Haikou, 570102, Hainan, China.
Li Ping JiaDepartment of Gynecology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China.
Yuzhu LiuDepartment of Gynecology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China.
Yiyu HanDepartment of Gynecology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China.
Qian LiDepartment of Clinical Laboratory, Wuhan Fourth Hospital, Puai Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan, Wuhan, China.
Qin ZouDepartment of Clinical Laboratory, Wuhan Fourth Hospital, Puai Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan, Wuhan, China.
Zhongpei ZhangDepartment of Clinical Laboratory, Wuhan Fourth Hospital, Puai Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan, Wuhan, China.
Jin HuangDepartment of Clinical Laboratory, Wuhan Fourth Hospital, Puai Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan, Wuhan, China. huangjintjmu@163.com.
Qingchun DengDepartment of Gynecology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China. qingchun0503@163.com.ORCID http://orcid.org/0000-0002-6700-7886
Hainan Medical University · CNWuhan Puai Hospital · CN

Funding

Applied basic research project of Wuhan Science and Technology Bureau 2019020701011472
6 · The paper itself

Abstract

backgroundIn this study we aimed to identify a prognostic signature in BRCA1/2 mutations to predict disease progression and the efficiency of chemotherapy ovarian cancer (OV), the second most common cause of death from gynecologic cancer in women worldwide.

methodsUnivariate Cox proportional-hazards and multivariate Cox regression analyses were used to identifying prognostic factors from data obtained from The Cancer Genome Atlas (TCGA) database. The area under the curve of the receiver operating characteristic curve was assessed, and the sensitivity and specificity of the prediction model were determined.

resultsA signature consisting of two long noncoding RNAs(lncRNAs), Z98885.2 and AC011601.1, was selected as the basis for classifying patients into high and low-risk groups (median survival: 7.2 years vs. 2.3 years). The three-year overall survival (OS) rates for the high- and low-risk group were approximately 38 and 100%, respectively. Chemotherapy treatment survival rates indicated that the high-risk group had significantly lower OS rates with adjuvant chemotherapy than the low-risk group. The one-, three-, and five-year OS were 100, 40, and 15% respectively in the high-risk group. The survival rate of the high-risk group declined rapidly after 2 years of OV chemotherapy treatment. Multivariate Cox regression associated with other traditional clinical factors showed that the 2-lncRNA model could be used as an independent OV prognostic factor. Analyses of data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) indicated that these signatures are pivotal to cancer development.

conclusionIn conclusion, Z98885.2 and AC011601.1 comprise a novel prognostic signature for OV patients with BRCA1/2 mutations, and can be used to predict prognosis and the efficiency of chemotherapy.

Indexed as

AdultAgedAged, 80 and overFemaleGenes, BRCA1HumansMiddle AgedOvarian NeoplasmsPrognosisRNA, Long NoncodingRNA, Long NoncodingBRCA1/2 geneChemotherapyEfficiencyLong non-coding RNAMutationsOvarian cancerPrognostic biomarker

Identifiers

PMID32950050
PMCPMC7502206
OpenAlexW3087537998

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.