Evidence map›Paper›PMID 28103585›Full record

ReviewOncotarget2017

Long non-coding RNAs in osteosarcoma.

Ruiling Chen, Gangyang Wang, Ying Zheng, Yingqi Hua, Zhengdong Cai

Open access · diamondAbstract readReview
In one paragraph

Review in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 1 pooled it
5.4field-weighted citation impact, top 3% 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

53 citing papers in PubMed, 1 synthesis or guideline pooled it, 92 citations in OpenAlex.

  1. Pooled it
  2. Review
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  4. Cancers · 2024
    Article
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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

5 authors at 2 institutions in 1 country.

Ruiling ChenDepartment of Orthopaedics, Shanghai Bone Tumor Institute, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Gangyang WangDepartment of Orthopaedics, Shanghai Bone Tumor Institute, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ying ZhengDepartment of Orthopaedics, Shanghai Bone Tumor Institute, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yingqi HuaDepartment of Orthopaedics, Shanghai Bone Tumor Institute, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhengdong CaiDepartment of Orthopaedics, Shanghai Bone Tumor Institute, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shanghai Jiao Tong University · CNShanghai First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) with more than 200 nuleotides, have been explored to participate in various cancer types including osteosarcoma (OS), which is the most common kind of primary bone tumors with high morbidity in infants and adolescents. These oncogenic or tumor suppressive lncRNAs regulate OS pathogenesis, such as cell growth, proliferation, invasion, migration, metastasis and cell apoptosis, serve as independent prognostic biomarkers or play a significant role in multidrug resistance (MDR) in OS cells. In this review, we attempt to dissect the participation of lncRNAs in pathogenesis of OS and their potential clinical values, and also provide an outlook for viable biomarkers and therapeutic targets in OS.

Indexed as

AnimalsBone NeoplasmsHumansOsteosarcomaRNA, Long NoncodingRNA, Long NoncodingbiomarkerslncRNAosteosarcomapathogenesistherapeutic targets

Identifiers

PMID28103585
PMCPMC5386777
OpenAlexW2575260040

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.