Evidence map›Paper›PMID 31772627›Full record

ArticleExperimental and therapeutic medicine2019

TOB1-AS1 suppresses non-small cell lung cancer cell migration and invasion through a ceRNA network.

Wen-Ji Shangguan, Hai-Tao Liu, Zu-Jun Que, Fang-Fang Qian, Ling-Shuang Liu, Jian-Hui Tian

Open access · diamondAbstract read
In one paragraph

Article in Experimental and therapeutic medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.5field-weighted citation impact, top 20% 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

18 citing papers in PubMed, 26 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Wen-Ji ShangguanDepartment of Oncology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, P.R. China.
Hai-Tao LiuDepartment of Oncology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, P.R. China.
Zu-Jun QueCancer Institute of Traditional Chinese Medicine, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, P.R. China.
Fang-Fang QianDepartment of Oncology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, P.R. China.
Ling-Shuang LiuDepartment of Oncology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, P.R. China.
Jian-Hui TianDepartment of Oncology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, P.R. China.
Shanghai University of Traditional Chinese Medicine · CNLonghua Hospital Shanghai University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-small cell lung cancer (NSCLC) is the leading cause of lung cancer-associated mortality. Recent studies revealed that long non-coding (lnc)RNAs have crucial roles in human cancers. The present study was the first, to the best of our knowledge, to indicate that the lncRNA transducer of ERBB2, 1-antisense 1 (TOB1-AS1) acts as a tumor suppressor in NSCLC. Knockdown of TOB1-AS1 significantly induced NSCLC cell migration, invasion and proliferation. It was also demonstrated that the higher expression of TOB1-AS1 in NSCLC samples was associated with longer overall survival time. Furthermore, a TOB1-AS1-mediated competing endogenous RNA network in NSCLC was constructed, including

Indexed as

competing endogenous RNA networklong non-coding RNAmetastasisnon-small cell lung cancertransducer of ERBB2 1 antisense 1

Identifiers

PMID31772627
PMCPMC6861872
OpenAlexW2980583921

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.