Females and Males Show Differences in Early-Stage Transcriptomic Biomarkers of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma.
LUAD
LUSC
early stage
sex disparity
transcriptomic biomarker
Journal
Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402
Informations de publication
Date de publication:
19 Feb 2021
19 Feb 2021
Historique:
received:
20
01
2021
revised:
15
02
2021
accepted:
17
02
2021
entrez:
6
3
2021
pubmed:
7
3
2021
medline:
7
3
2021
Statut:
epublish
Résumé
The incidence and mortality rates of lung cancers are different between females and males. Therefore, sex information should be an important part of how to train and optimize a diagnostic model. However, most of the existing studies do not fully utilize this information. This study carried out a comparative investigation between sex-specific models and sex-independent models. Three feature selection algorithms and five classifiers were utilized to evaluate the contribution of the sex information to the detection of early-stage lung cancers. Both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) showed that the sex-specific models outperformed the sex-independent detection of early-stage lung cancers. The Venn plots suggested that females and males shared only a few transcriptomic biomarkers of early-stage lung cancers. Our experimental data suggested that sex information should be included in optimizing disease diagnosis models.
Identifiants
pubmed: 33669819
pii: diagnostics11020347
doi: 10.3390/diagnostics11020347
pmc: PMC7922551
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Jilin Provincial Key Laboratory of Big Data Intelligent Computing
ID : 20180622002JC
Organisme : Education Department of Jilin Province
ID : JJKH20180145KJ
Organisme : Jilin University
ID : startup
Organisme : Bioknow MedAI Institute
ID : BMCPP-2018-001
Organisme : Jilin University
ID : High Performance Computing Center
Organisme : Fundamental Research Funds for the Central Universities
ID : JLU
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