ArticleBulletin of experimental biology and medicine2021
Microarray Analysis of Novel Genes Involved in Nasopharyngeal Carcinoma.
Article in Bulletin of experimental biology and medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Prognostic and Clinicopathological Value of ZWINT Expression Levels in Patients with Lung Adenocarcinoma: A Systematic Review and Meta-analysis.Clinics (Sao Paulo, Brazil) · 2021Pooled it
- Association of ZWINT Expression with Clinicopathologic Characteristics and Prognosis in Breast Cancer Patients.Current medical science · 2025Article
- Identification and validation of anoikis-related differentially expressed genes in nasopharyngeal carcinoma.Translational cancer research · 2025Article
- Knockdown of RFC4 inhibits the cell proliferation of nasopharyngeal carcinoma in vitro and in vivo.Frontiers of medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nasopharyngeal carcinoma (NPC) is an epithelial cancer associated with Epstein-Barr virus. Despite NPC is a widespread malignancy, little is known about association of tumor growth with gene expression. This study is aimed to detect potential genes implicated in the molecular mechanism of NPC. To this end, we downloaded GSE12452, GSE53819 and GSE64634 libraries from GEO database. GEO2R interface was used to search for the differentially expressed genes (DEGs) with R and LIMMA software, which yielded the Venn diagrams of co-expressed genes. The GO and KEGG databases were used to find DEGs with up- and down-regulated expression. Then Cytoscape software constructed and analyzed the protein-protein interaction (PPI) networks corresponding to revealed DEGs, thereupon the hub genes were analyzed in tissues and cell cultures with qRT-PCR. This combined analysis yielded 483 co-expressed DEGs, including 258 DEGs with up-regulated expression and 225 DEGs with down-regulated expression, which are mainly implicated in the cell cycle, DNA replication, as well as in formation and maturation of extracellular vesicles and exosomes. In comparison with normal nasopharyngeal tissues of healthy persons, expression of CDK1 gene was down-regulated in NPC tissue; in contrast, expression of PCNA, MAD2L1, PRC1, CENPF, and ZWINT genes was up-regulated in the tumor. The genes PCNA, MAD2L1, and ZWINT were differently expressed in EBV+ and EBV- nasopharyngeal carcinoma cells. The use of bioinformatic methods to reveal and analyze the differences in gene expression between the normal and NPC tissues opens the vista to further progress in deciphering the molecular mechanisms of NPC formation and development.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.