Evidence map›Paper›PMID 36101427›Full record

ArticleBiology2022

Abnormal Gene Expression Regulation Mechanism of Myeloid Cell Nuclear Differentiation Antigen in Lung Adenocarcinoma.

Zhongxiang Tang, Lili Wang, Ousman Bajinka, Guojun Wu, Yurong Tan

Open access · goldAbstract read
In one paragraph

Article in Biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 18 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

5 authors at 1 institution in 1 country.

Zhongxiang TangDepartment of Medical Microbiology, School of Basic Medical Sciences, Central South University, Changsha 410078, China.
Lili WangDepartment of Medical Microbiology, School of Basic Medical Sciences, Central South University, Changsha 410078, China.
Ousman BajinkaDepartment of Medical Microbiology, School of Basic Medical Sciences, Central South University, Changsha 410078, China.ORCID 0000-0002-2871-4078
Guojun WuDepartment of Medical Microbiology, School of Basic Medical Sciences, Central South University, Changsha 410078, China.
Yurong TanDepartment of Medical Microbiology, School of Basic Medical Sciences, Central South University, Changsha 410078, China.ORCID 0000-0002-0283-2105
Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma (LA) is the main pathological type of lung cancer with a very low 5-year survival rate. In the present study, after downloading the mRNA, miRNA, and DNA methylation sequencing data from TCGA, combined with the downloaded clinical data, comparative analysis, prognostic analysis, GO and KEGG analysis, GSEA analysis, methylation analysis, transcriptional regulation and post-transcriptional regulation were performed. We found that both methylation and gene expression of MNDA in LA were down-regulated, while high expression of MNDA was associated with good overall survival in LA. To probe the mechanism, further analysis showed that SPI1 was the main transcription factor of MNDA, but it was also down-regulated in LA. At the same time, the expression of eight target miRNAs of MNDA was significantly up-regulated, and the expression of hsa-miR-33a-5p and hsa-miR-33b-5p were verified to directly target MNDA. In conclusion, the abnormal expression of MNDA in LA is the result of the combined effects of transcriptional and post-transcriptional regulation.

Indexed as

gene methylationlung adenocarcinomamiRNAmyeloid cell nuclear differentiation antigenSPI1

Identifiers

PMID36101427
PMCPMC9312870
OpenAlexW4285392225

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.