Evidence map›Paper›PMID 28389671›Full record

ArticleScientific reports2017

Identification of a six-lncRNA signature associated with recurrence of ovarian cancer.

Kai Yang, Yan Hou, Ang Li, Zhenzi Li, Wenjie Wang, Hongyu Xie, Zhiwei Rong, Ge Lou, Kang Li

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
–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

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Long noncoding RNAs in female malignancies: critical review of molecular mechanisms, clinical gaps, and therapeutic perspectives.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  16. Long Noncoding RNAs as Innovative Urinary Diagnostic Biomarkers.Methods in molecular biology (Clifton, N.J.) · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Kai YangDepartment of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, P.R. China.
Yan HouDepartment of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, P.R. China.
Ang LiDepartment of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, P.R. China.
Zhenzi LiDepartment of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, P.R. China.
Wenjie WangDepartment of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, P.R. China.
Hongyu XieDepartment of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, P.R. China.
Zhiwei RongDepartment of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, P.R. China.
Ge LouDepartment of Gynecology Oncology, the Tumor Hospital, Harbin Medical University, Harbin, 150086, P.R. China. likang@ems.hrbmu.edu.cn.
Kang LiDepartment of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, P.R. China. louge@ems.hrbmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer (OvCa) is the leading cause of death among all gynecological malignancies, and recurrent OvCa is almost always incurable. In this study, we developed a signature based on long non-coding RNAs (lncRNAs) associated with OvCa recurrence to facilitate personalized OvCa therapy. lncRNA expression data were extracted from GSE9891 and GSE30161. LASSO (least absolute shrinkage and selection operator) penalized regression was used to identify an lncRNA-based signature using the GSE9891 training cohort. The signature was then validated in GSE9891 internal and GSE30161 external validation cohorts. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to explore the possible functions of identified lncRNAs. A six-lncRNA signature (RUNX1-IT1, MALAT1, H19, HOTAIRM1, LOC100190986 and AL132709.8) was identified in the training cohort and validated in internal and external validation cohorts using the LASSO method (P < 0.05). This signature was also independent of other clinical factors according to multivariate and sub-group analyses. The identified lncRNAs are involved in cancer-related biological processes and pathways. We selected a highly reliable signature based on six lncRNAs associated with OvCa recurrence. This six-lncRNA signature is a promising method to personalize ovarian cancer therapy and may improve patient quality of life quality according to patients' condition in the future.

Identifiers

PMID28389671
PMCPMC5429632

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