Evidence map›Paper›PMID 32194727›Full record

ArticleOncology letters2020

Long non-coding (lnc)RNA PAPAS overexpression inhibits tumor growth in papillary thyroid carcinoma by downregulating lncRNA HOTTIP.

Juan Xiao, Zhaowei Bing, Ge Xiao, Yang Guan, Jian Luan

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 48% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
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  4. Review
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 3 institutions in 1 country.

Juan XiaoDepartment of Endocrinology, Qingdao Municipal Hospital, Qingdao, Shandong 266000, P.R. China.
Zhaowei BingDepartment of Endocrinology, Qingdao Municipal Hospital, Qingdao, Shandong 266000, P.R. China.
Ge XiaoDepartment of Neurology, Qianfoshan Hospital Affiliated to Shandong University, Jinan, Shandong 250014, P.R. China.
Yang GuanDepartment of Static Distribution Center, Qingdao Municipal Hospital, Qingdao, Shandong 266000, P.R. China.
Jian LuanDepartment of Endocrinology, Qingdao Municipal Hospital, Qingdao, Shandong 266000, P.R. China.
Qingdao University · CNQingdao Municipal Hospital · CNShandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The long non-coding (lnc)RNA pre-ribosomal RNA antisense transcripts (PAPAS) can repress ribosomal RNA synthesis, although its role in human disease is currently unknown. The present study aimed to investigate the function of PAPAS in papillary thyroid carcinoma (PTC). PAPAS was downregulated, while the lncRNA HOXA transcript at the distal tip (HOTTIP) was upregulated in patients with PTC. PAPAS and HOTTIP were inversely associated in PTC. PAPAS overexpression led to the downregulation of HOTTIP in PTC cells, while PAPAS expression was not significantly affected by HOTTIP overexpression, suggesting that PAPAS was upstream of HOTTIP. PAPAS expression level decreased, while HOTTIP expression level increased with the increase of clinical staging. PAPAS overexpression led to the inhibition of cell proliferation, while HOTTIP overexpression increased proliferation of PTC cells, and HOTTIP overexpression decreased the effects of PAPAS overexpression. lncRNA PAPAS overexpression may inhibit tumor growth in papillary thyroid carcinoma by downregulating lncRNA HOTTIP.

Indexed as

long non-coding RNA HOXA transcript at the distal tiplong non-coding RNA pre-ribosomal RNA antisense transcriptspapillary thyroid carcinomaproliferation

Identifiers

PMID32194727
PMCPMC7039133
OpenAlexW3002181873

What OpenQuestion holds

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Registered trials

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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.