Evidence map›Paper›PMID 35116553›Full record

ArticleTranslational cancer research2021

Long noncoding RNA DATOC-1 that associate with DICER promotes development in epithelial ovarian cancer by upregulating miR-7 expression.

Wenxing Qin, Yuqing Miao, Guangxia Sun, Shiqi Chen, Yuan-Sheng Zang, Chao Dong

Open access · diamondAbstract read
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Article in Translational cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 47% of its field
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

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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 4 institutions in 1 country.

Wenxing Qin *Department of Medical Oncology, Changzheng Hospital, Navy Medical University, Shanghai, China.
Yuqing Miao *Department of Medical Oncology, Changzheng Hospital, Navy Medical University, Shanghai, China.
Guangxia Sun *Assistant Clerk of Medical Administration Division, Changzheng Hospital, Navy Medical University, Shanghai, China.
Shiqi ChenDepartment of Medical Oncology, Changzheng Hospital, Navy Medical University, Shanghai, China.
Yuan-Sheng ZangDepartment of Medical Oncology, Changzheng Hospital, Navy Medical University, Shanghai, China.
Chao DongDepartment of the Second Medical Oncology, The 3rd Affiliated Hospital of Kunming Medical University, Yunnan Tumor Hospital, Kunming, China.
Shanghai Changzheng Hospital · CNKunming Medical University · CNNantong University · CNShanghai Institute of Pharmaceutical Industry · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDICER is a key RNase III enzyme that cleaves processes miRNAs into their mature form. It is remarkably down-regulated in most epithelial ovarian cancer (EOC) and the down-regulation is associated with high grade malignancy as well as poor clinical outcomes. In this study, we aimed to discover a lncRNA interacting with DICER to participate in the process of microRNAs maturation and as a result promoting development of EOC.

methodsWe conducted a RIP-seq aimed at DICER and we obtained its chromosomal location by aligning the sequence in PubMed. And the lncRNA was named DATOC-1 (DICER Associated Transcript 1 in Ovarian Cancer). We tested relative expression of DATOC-1 in 53 EOC and 7 adjacent ovarian samples by qRT-PCR. Then the expression in EOC patients derived from The Cancer Genome Atlas (TCGA) were analysed to identify DATOC-1-based signatures for EOC prognosis with survival analysis. Lastly, shRNA Screening and lentiviral transduction was used to determine the function of DATOC-1

resultsWe identified the lncRNA RP5-1120P11.1 as DATOC-1, which highly expressed in EOC tissues than in adjacent. And Kaplan-Meier analysis indicated that the patients with EOC that expressed high levels of DATOC-1 had a worse prognosis and shorter disease OS compared with DATOC-1 low-expressed patients. In addition, DATOC-1 were further identified participating in EOC cell proliferation, cell cycle regulation and cell invasion. And knockdown of DATOC-1 inhibits tumor progression

conclusionsOur research shows that DATOC-1 can inhibit the development of EOC and is a promising therapeutic target.

Indexed as

DICERepithelial ovarian cancer (EOC)LncRNA DATOC-1miR7target

Identifiers

PMID35116553
PMCPMC8798263
OpenAlexW3164602478

What OpenQuestion holds

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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.