Evidence map›Paper›PMID 36221371›Full record

ArticleMedicine2022

Systematic investigation of the clinical significance and prognostic value of the CBXs in esophageal cancer.

Jun Hou, Yinfeng Yang, Honglei Gao, Ting Ouyang, Qiwei Liu, Ran Ding, Hongxing Kan

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2022. 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
0.3field-weighted citation impact, top 47% 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, 4 citations in OpenAlex.

  1. Article
  2. CBX6 induces CD8Cell biology and toxicology · 2025
    Article
  3. Review
  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

7 authors at 1 institution in 1 country.

Jun HouSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China.ORCID 0000-0002-8832-7758
Yinfeng YangSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China.
Honglei GaoSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China.
Ting OuyangSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China.
Qiwei LiuSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China.
Ran DingSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China.
Hongxing KanSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China.
Anhui University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Esophageal cancer (ESCA), one of the most aggressive malignant tumors, has been announced to be the ninth most common cancer and the sixth leading cause of cancer-related death in the world. Chromobox family members (CBXs) are important epigenetic regulators which are related with the transcription of target genes. The role of CBXs in carcinomas has been reported in many studies. However, the function and prognostic value of different CBXs in ESCA are still largely unknown. In this article, we first performed differential expression analysis through several methods including Oncomine and Gene Expression Profiling Interactive Analysis. The results led us to determine the differential expression of CBXs in pan-cancer, especially ESCA. Then we evaluated the prognostic value of different CBX messenger RNA (mRNA) expression in patients with ESCA through the Kaplan-Meier plotter and the Human Protein Atlas database. In addition, we used cBioPortal to explore all genetic alterations and mutations in the CBXs in ESCA. Simultaneously, the correlation between its expression and the level of immune infiltration of ESCA was visualized by TIMER. Finally, the biological function of CBXs in ESCA is obtained through Biological Enrichment Analysis including gene ontology and Kyoto Encyclopedia of Genes and Genomes. The expression levels of CBX3/4/5 and CBX8 in ESCA tissues increased significantly and the expression level of CBX7 decreased through differential expression analysis. Additionally, CBX1 is significantly related to the clinical cancer stage and disease-free survival of ESCA patients. The high mRNA expression of CBX4 is related to the short overall survival of patients with esophageal squamous cell carcinoma, and the high mRNA expression of CBX3/7/8 is related to the short overall survival of patients with esophageal adenocarcinoma, indicating that CBX1/3/4/7/8 may be a potential prognostic biomarker for the survival of ESCA patients. Besides, the expression of CBXs is significantly related to the infiltration of a variety of immune cells, including six types of CD4-positive T-lymphocytes, macrophages, neutrophils, bursindependentlymphocyte, CD8-positive T-lymphocytes cells and dendritic cells in ESCA. Moreover, we found that CBXs are mainly associated with the inhibition of cell cycle and apoptosis pathway. Further, enrichment analysis indicated that CBXs and correlated genes were enriched in mismatch repair, DNA replication, cancer pathways, and spliceosomes. Our research may provide new insights into the choice of prognosis biomarkers of the CBXs in ESCA.

Indexed as

Esophageal NeoplasmsEsophageal Squamous Cell CarcinomaBiomarkersChromosomal Proteins, Non-HistoneHumansLigasesPolycomb-Group ProteinsPolycomb Repressive Complex 1PrognosisRNA, MessengerBiomarkersCBX3 protein, humanCBX4 protein, humanCBX7 protein, humanCBX8 protein, humanChromosomal Proteins, Non-HistoneLigasesPolycomb-Group ProteinsPolycomb Repressive Complex 1RNA, Messenger

Identifiers

PMID36221371
PMCPMC9542684
OpenAlexW4304091606

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.