Evidence map›Paper›PMID 35117529›Full record

ArticleTranslational cancer research2020

A transcriptomic analysis of malignant transformation of human embryonic esophageal epithelial cells by HPV18 E6E7.

Duo Tang, Biqi Wang, Sara Khodahemmati, Jingtao Li, Zhixiang Zhou, Jingfeng Gao, Wang Sheng, Yi Zeng

Open access · diamondAbstract read
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Article in Translational cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 32% 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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Duo TangCollege of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China.
Biqi WangCollege of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China.
Sara KhodahemmatiCollege of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124, China.
Jingtao LiCollege of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China.
Zhixiang ZhouCollege of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China.
Jingfeng GaoCollege of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124, China.
Wang ShengCollege of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China.
Yi ZengCollege of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China.
Beijing University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEsophageal cancer is one of the most common malignant tumours in humans. A series of esophageal cancer cell lines are accompanied by human papilloma virus (HPV) infection, but the mechanism behind HPV in cancer malignancy is not clear.

methodsThis research was conducted in different generations of HPV E6E7 gene-induced human foetal esophageal epithelial immortalised cells (Shantou Human Embryonic Esophageal Epithelial cell line; SHEE); the RNA sequencing transcriptomic analysis was performed to explore the mechanism of HPV infection in these cell lines.

resultsThe results showed that there are 9,990 differential genes in late-stage cells compared with HPV18 E6E7-infected early foetal esophageal epithelial immortalised cells. Among these, 4,882 genes are upregulated, and 5,108 genes are downregulated. We used bioinformatics to analyze the expression and function of aberrantly expressed lncRNA, miRNA, mRNA and construct the competing endogenous RNA (ceRNA) network and protein protein interaction (PPI) network.

conclusionswe predicted TP53TG1 promotes to malignant transformation of SHEEs by acting as a ceRNA to competitively bind to miR-6835 and regulate IGF2 expression. We also predicted IL6 serve as prognostic biomarkers and therapy target. With these results maybe provides new insights into the mechanisms of HPV carcinogenesis in esophageal cancer.

Indexed as

esophageal cancerHuman papilloma virus (HPV)qRT-PCRRNA-Seq

Identifiers

PMID35117529
PMCPMC8797993
OpenAlexW3009853067

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.