Evidence map›Paper›PMID 26622675›Full record

ArticleOncology letters2015

Pathogenic mechanisms of lung adenocarcinoma in smokers and non-smokers determined by gene expression interrogation.

Yunqian Hu, Guohan Chen

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

17 citing papers in PubMed, 30 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

2 authors at 2 institutions in 1 country.

Yunqian HuDepartment of Respiration, East Hospital, Tongji University School of Medicine, Shanghai 200120, P.R. China.
Guohan ChenDepartment of Thoracic Surgery, East Hospital, Tongji University School of Medicine, Shanghai 200120, P.R. China.
Shanghai East Hospital · CNTongji University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cigarette smoking is the leading risk factor for lung cancer, which accounts for the highest number of cancer-related mortalities worldwide in men and women. Individuals with a history of smoking are 15-30 times more likely to develop lung cancer compared with those who do not smoke. However, our understanding of the underlying molecular mechanisms that contribute to lung tumorigenesis in smokers versus non-smokers remains incomplete. In order to investigate such mechanisms, the present study aimed to systemically interrogate microarray datasets from tumor biopsies and matching normal tissues from stage I and II lung adenocarcinoma patients who had never smoked or were current smokers. The gene expression analysis identified 422 (99 upregulated and 323 downregulated) and 534 (174 upregulated and 360 downregulated) differentially-expressed genes from the never-smokers and current smokers, respectively, and the two groups shared 277 genes that exhibited similar trends of alteration. These genes encode regulators that are involved in a variety of cellular functions, including collagen metabolism and homeostasis of caveolae plasma membranes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes characterization indicated that biological pathways, including extracellular matrix-receptor interaction and cell migration and proliferation, were all affected in the lung cancer patients regardless of the smoking status. However, smoking induced a unique gene expression pattern characterized by upregulation of cell cycle regulators (

Indexed as

cell proliferationlung adenocarcinomamicroarray analysisp53smoking

Identifiers

PMID26622675
PMCPMC4533670
OpenAlexW1946541987

What OpenQuestion holds

Textmetadata
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.