Evidence map›Paper›PMID 30452402›Full record

ArticleCancer biomarkers : section A of Disease markers2019

Long noncoding RNA HOTTIP is a significant indicator of ovarian cancer prognosis and enhances cell proliferation and invasion.

Ting Zou, Ping Ling Wang, Yan Gao, Wen Tong Liang

Abstract read
In one paragraph

Article in Cancer biomarkers : section A of Disease markers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

25 citing papers in PubMed, 40 citations in OpenAlex.

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  19. Knockdown of DANCR Suppressed the Biological Behaviors of Ovarian Cancer Cells Treated with Transforming Growth Factor-β (TGF-β) by Sponging MiR-214.Medical science monitor : international medical journal of experimental and clinical research · 2020
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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

4 authors.

Ting Zou
Ping Ling Wang
Yan Gao
Wen Tong Liang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long noncoding RNAs (LncRNAs) are involved in the occurrence and progression of human tumors including ovarian cancer (OC). Long noncoding RNA HOTTIP has been found to be involved in several human tumors development. However, the role of HOTTIP in OC remains large unknown. In the present study, our results observed that lncRNA HOTTIP expression levels were notably higher in ovarian cancer tissue samples compared to adjacent normal tissue samples. Increased lncRNA HOTTIP expression levels were significantly associated with advanced FIGO stage and lymph node metastasis of ovarian cancer patients. Survival plots analysis results showed high lncRNA HOTTIP expression levels in ovarian cancer patients showed a poor prognosis compared to patients with low lncRNA HOTTIP expression levels. Function assays showed that lncRNA HOTTIP knockdown in ovarian cancer cells decreased cell proliferation and cell invasion capacities. Furthermore, we demonstrated that inhibition of lncRNA HOTTIP suppressed Wnt/β-catenin signaling by downregulating β-catenin expression. Thus, these results suggest that aberrant HOTTIP expression level could serve as a promising biomarker for monitoring ovarian cancer and potential target of ovarian cancer treatment.

Indexed as

Biomarkers, TumorAdultAgedBiomarkersCell CycleCell Line, TumorCell MovementCell ProliferationFemaleGene Expression Regulation, NeoplasticHumansMiddle AgedNeoplasm GradingNeoplasm MetastasisNeoplasm StagingOvarian NeoplasmsBiomarkersBiomarkers, Tumorlong noncoding RNA HOTTIP, humanRNA, Long Noncodingcell proliferationHOTTIPlong noncoding RNAOvarian cancerprognosis

Identifiers

PMID30452402
PMCPMC13082406
OpenAlexW2901573718

What OpenQuestion holds

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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.