Evidence map›Paper›PMID 30556321›Full record

ArticleMolecular genetics & genomic medicine2019

Identification of genes associated with cancer progression and prognosis in lung adenocarcinoma: Analyses based on microarray from Oncomine and The Cancer Genome Atlas databases.

Wei Liu, Songyun Ouyang, Zhigang Zhou, Meng Wang, Tingting Wang, Yu Qi, Chunling Zhao, Kuisheng Chen, Liping Dai

Abstract read
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Article in Molecular genetics & genomic medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

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34citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

34 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

9 authors.

Wei LiuDepartment of Gastroenterology in the First Affiliated Hospital, Zhengzhou University, Zhengzhou, China.
Songyun OuyangDepartment of Respiratory and Sleep Medicine in the First Affiliated Hospital, Zhengzhou University, Zhengzhou, China.
Zhigang ZhouDepartment of Radiology in the First Affiliated Hospital, Zhengzhou University, Zhengzhou, China.
Meng WangDepartment of Radiology in the First Affiliated Hospital, Zhengzhou University, Zhengzhou, China.
Tingting WangDepartment of Medical Examination in the First Affiliated Hospital, Zhengzhou University, Zhengzhou, China.
Yu QiDepartment of Thoracic Surgery in the First Affiliated Hospital, Zhengzhou University, Zhengzhou, China.
Chunling ZhaoDepartment of Respiratory and Sleep Medicine in the First Affiliated Hospital, Zhengzhou University, Zhengzhou, China.
Kuisheng ChenDepartment of Pathology in the First Affiliated Hospital, Zhengzhou University, Zhengzhou, China.
Liping DaiDepartment of Respiratory and Sleep Medicine in the First Affiliated Hospital, Zhengzhou University, Zhengzhou, China.ORCID 0000-0002-5531-1776

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung adenocarcinoma (LUAD) accounts for approximately 40% of all lung cancer patients. There is an urgent need to understand the mechanisms of cancer progression in LUAD and to identify useful biomarkers to predict prognosis.

methodsIn this study, Oncomine database was used to identify potential genes contributed to cancer progression. Bioinformatics analysis including pathway enrichment and text mining was used to explain the potential roles of identified genes in LUAD. The Cancer Genome Atlas database was used to analyze the association of gene expression with survival result.

resultsOur results indicated that 80 genes were significantly dysregulated in LUAD according to four microarrays covering 356 cases of LUAD and 164 cases of normal lung tissues. Twenty genes were consistently and stably dysregulated by more than twofold. Ten of 20 genes had a relationship with overall survival or disease-free survival in a cohort of 516 LUAD patients, and 19 genes were associated with tumor stage, gender, age, lymph node, or smoking. Low expression of AGER and high expression of CCNB1 were specifically associated with poor survival.

conclusionOur findings implicate AGER and CCNB1 might be potential biomarkers for diagnosis and prognosis targets for LUAD.

Indexed as

Gene Expression Regulation, NeoplasticAdenocarcinomaBiomarkers, TumorCyclin B1Databases, GeneticHumansLungLung NeoplasmsReceptor for Advanced Glycation End ProductsAGER protein, humanBiomarkers, TumorCCNB1 protein, humanCyclin B1Receptor for Advanced Glycation End Productsbiomarkerlung adenocarcinomamicroarrayprognosis

Identifiers

PMID30556321
PMCPMC6393652

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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.