Evidence map›Paper›PMID 36092901›Full record

ArticleFrontiers in genetics2022

NcRNA-mediated upregulation of CAMK2N1 is associated with poor prognosis and tumor immune infiltration of gastric cancer.

Kaipeng Peng, Xiangqing Ren, Qian Ren

Open access · goldAbstract read
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Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 33% 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

6 citing papers in PubMed, 8 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

3 authors at 2 institutions in 1 country.

Kaipeng PengThe First Clinical Medical College, Lanzhou University, Lanzhou, China.
Xiangqing RenThe First Clinical Medical College, Lanzhou University, Lanzhou, China.
Qian RenThe First Clinical Medical College, Lanzhou University, Lanzhou, China.
Lanzhou University · CNFirst Hospital of Lanzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancer (GC) is still notorious for its poor prognosis and aggressive characteristics. Though great developments have been made in diagnosis and therapy for GC, the prognosis of patient is still perishing. In this study, differentially expressed genes (DEGs) in GC were first screened using three Gene Expression Omnibus (GEO) datasets (GSE13911, GSE29998, and GSE26899). Second, The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) data were used to validate expression of these DEGs and perform survival analysis. We selected seven candidate genes (CAMK2N1, OLFML2B, AKR7A3, CYP4X1, FMO5, MT1H, and MT1X) to carry out the next analysis. To construct the ceRNA network, we screened the most potential upstream ncRNAs of the candidate genes. A series of bioinformatics analyses, including expression analysis, correlation analysis, and survival analysis, revealed that the SNHG10-hsa-miR-378a-3p might be the most potential regulatory axis in GC. Then, the expression of CAMK2N1, miR-378a-3p, and SNHG10 was verified in GC cell lines (GES-1, MGC-803, BGC-823, HGC-27, MKN-45, and AGS) by qRT-PCR and Western blotting. We found that SNHG10 and CAMK2N1 were highly expressed in gastric cancer lines, and the miR-378a-3p was lowly expressed in BGC-823, HGC-27, and MKN-45. Furthermore, CAMK2N1 levels were significantly negatively associated with tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression. In summary, our results suggest that the ncRNA-mediated high expression of CAMK2N1 is associated with poor prognosis and tumor immune infiltration of GC.

Indexed as

CAMK2N1gastric cancernoncoding RNAprognosistumor immune infiltration

Identifiers

PMID36092901
PMCPMC9452964
OpenAlexW4293018413

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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.