Evidence map›Paper›PMID 31641374›Full record

ArticleBioData mining2019

Integrative analysis of genetic and epigenetic profiling of lung squamous cell carcinoma (LSCC) patients to identify smoking level relevant biomarkers.

Bidong Ma, Zhiyou Huang, Qian Wang, Jizhou Zhang, Bin Zhou, Jiaohong Wu

Abstract read
In one paragraph

Article in BioData mining, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

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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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. [Research Progress of Epigenetics in Pathogenesis and Treatment of Malignant Tumors].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2020
    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

6 authors.

Bidong MaDepartment of Medical Oncology, Zhe Jiang Chinese Medicine University affiliated Chinese Medicine Hospital, Wen Zhou, Zhe Jiang province People's Republic of China.
Zhiyou HuangDepartment of Medical Oncology, Zhe Jiang Chinese Medicine University affiliated Chinese Medicine Hospital, Wen Zhou, Zhe Jiang province People's Republic of China.
Qian WangTianjia Genomes Tech CO., LTD., No. 6 Longquan Road, Anhui Chaohu economic develop zone, Hefei, 238014 People's Republic of China.
Jizhou ZhangDepartment of Medical Oncology, Zhe Jiang Chinese Medicine University affiliated Chinese Medicine Hospital, Wen Zhou, Zhe Jiang province People's Republic of China.
Bin ZhouDepartment of Medical Oncology, Zhe Jiang Chinese Medicine University affiliated Chinese Medicine Hospital, Wen Zhou, Zhe Jiang province People's Republic of China.
Jiaohong Wu3Department of Gynecology and Oncology, Wen Zhou Medical University affiliated People's Hospital, Wen Zhou, Zhe Jiang province People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIncidence and mortality of lung cancer have dramatically decreased during the last decades, yet still approximately 160,000 deaths per year occurred in United States. Smoking intensity, duration, starting age, as well as environmental cofactors including air-pollution, showed strong association with major types of lung cancer. Lung squamous cell carcinoma is a subtype of non-small cell lung cancer, which represents 25% of the cases. Thus, exploring the molecular pathogenic mechanisms of lung squamous cell carcinoma plays crucial roles in lung cancer clinical diagnosis and therapy.

resultsIn this study, we performed integrative analyses on 299 comparative datasets of RNA-seq and methylation data, collected from 513 lung squamous cell carcinoma cases in The Cancer Genome Atlas. The data were divided into high and low smoking groups based on smoking intensity (Numbers of packs per year). We identified 1002 significantly up-regulated genes and 534 significantly down-regulated genes, and explored their cellular functions and signaling pathways by bioconductor packages GOseq and KEGG. Global methylation status was analyzed and visualized in circular plot by CIRCOS. RNA-and methylation data were correlatively analyzed, and 24 unique genes were identified, for further investigation of regional CpG sites' interactive patterns by bioconductor package coMET. AIRE, PENK, and SLC6A3 were the top 3 genes in the high and low smoking groups with significant differences.

conclusionsGene functions and DNA methylation patterns of these 24 genes are important and useful in disclosing the differences of gene expression and methylation profiling caused by different smoking levels.

Indexed as

Data miningLung squamous cell carcinomaMethylationRNA-seqSmoking intensityThe Cancer genome atlas

Identifiers

PMID31641374
PMCPMC6802182

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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.