Evidence map›Paper›PMID 30618123›Full record

ArticleJournal of cellular physiology2019

Four lncRNAs associated with breast cancer prognosis identified by coexpression network analysis.

Jie Li, Chundi Gao, Cun Liu, Chao Zhou, Xiaoran Ma, Huayao Li, Jia Li, Xue Wang, Lingyu Qi, Yan Yao and 5 more

Abstract read
In one paragraph

Article in Journal of cellular physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

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

  1. Pooled it
  2. Exosomal lncRNAsInternational journal of molecular sciences · 2026
    Article
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  19. OncoTargets and therapy · 2019
    Review
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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

15 authors.

Jie LiCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, P. R. China.
Chundi GaoCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, P. R. China.
Cun LiuCollege of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, P. R. China.
Chao ZhouDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong, P. R. China.
Xiaoran MaCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, P. R. China.
Huayao LiCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, P. R. China.
Jia LiClinical Medical Colleges, Weifang Medical University, Weifang, Shandong, P. R. China.
Xue WangCollege of Basic Medicine, Qingdao University, Qingdao, Shandong, P. R. China.
Lingyu QiCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, P. R. China.
Yan YaoClinical Medical Colleges, Weifang Medical University, Weifang, Shandong, P. R. China.
Xiaoming ZhangCollege of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, P. R. China.
Jing ZhuangDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong, P. R. China.
Lijuan LiuDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong, P. R. China.
Kejia WangCollege of Basic Medicine, Qingdao University, Qingdao, Shandong, P. R. China.
Changgang SunDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong, P. R. China.ORCID 0000-0003-0778-8788

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies on long noncoding RNA (lncRNA) have made breakthroughs in the treatment of several tumors, and these findings have brought attention to the lncRNA signature of breast cancer. Increased understanding of genomic architecture and achievement of innovative therapeutic strategies has prompted creation of a novel oncological model for the treatment of solid cancers. In this study, we systematically analyzed the transcriptome of breast cancer tissues to gain more in-depth knowledge of tumor biology. Gene coexpression relationships were studied in 206 samples from The Cancer Genome Atlas database, and nine coexpression modules were identified. After screening and analysis, we identified four important prognosis-related lncRNAs (HOTAIR, SNHG16, HCP5, and TINCR), and constructed a prognostic model, one (HCP5) of which has not previously been identified in the context of breast cancer. Importantly, an understanding of prognosis facilitates precise disease risk assessment and advances the selection of strategies for risk-adaptive management. These findings broaden the landscape of carcinogenic lncRNAs in breast cancer, providing insights into the biological significance and clinical application of lncRNAs in breast cancer.

Indexed as

Gene Expression Regulation, NeoplasticGene Regulatory NetworksBreast NeoplasmsFemaleGene Expression ProfilingHumansKaplan-Meier EstimateOpen Reading FramesPrognosisRisk FactorsRNA, Long NoncodingROC CurveRNA, Long Noncodingbreast cancergene coexpressionlncRNA

Identifiers

PMID30618123
PMCPMC13483020

What OpenQuestion holds

Textmetadata
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.